This PDF file contains the front matter associated with SPIE Proceedings Volume 12557, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

The paper proposes an empirical mode decomposition (EMD)-wavelet algorithm for the noise suppression of the PDH error signal. The EMD is used to decompose the PDH error signal into a finite number of intrinsic mode functions. The Daubechies 4 wavelet is used to suppress the noise in the intrinsic mode functions. A FBG based Fabry-Perot interferometer is used as the sensing element. A narrow linewidth tunable laser is used as the laser source. The laser is phase modulated by a sinusoidal signal. A lock-in amplifier is used to extract the PDH error signal. A proportional-integral-derivative controller is used to control the laser frequency. The noise in the PDH error signal is effectively suppressed. Moreover, the signal-noise-ratio (SNR) of the PDH error signal is improved from 16 dB to 28 dB. A strain signal (1 nε) is applied on the FBG-FP via a PZT. A high-resolution of 680 fε/√Hz@ 1 kHz is achieved.

According to the CMOS image sensor (CIS) high linearity, low power consumption, and consistent loading requirement, this paper proposed an analog-to-digital-converter (ADC) implement circuit that integrated in CIS. The proposed ADC aims to achieve high linearity as well as low power consumption or consistent power source loading. In the readout chain, every column has an independent programmable-gain-amplifier (PGA), an ADC comparator, and an ADC counter. However, all the columns share a ramp generator to provide a ramp reference to the ADC comparator. The proposed high linearity ADC is optimized through a ramp kick back noise compensation technique, a load balance technique. In addition, low power consumption mode is an optional for circumstance requires low power consumption.

In the infrared ship target detection task, natural interference such as fish scale light, bright sea surface, clouds, and rainfall are prone to occur in the scene. Common detection algorithms focus on the target area and ignore the effective information in other areas of the image, so it is difficult to effectively deal with the interference of complex infrared scenes on the sea surface. In this paper, “semantic segmentation” is introduced into the field of infrared ship target detection, and the characteristics of global image processing of semantic segmentation are used to obtain deep semantic information of images. Combined with prior theory, Scene-Aware Prior semantic segmentation Network (SAPN) is proposed. In addition, a dataset of infrared ship target semantic segmentation is constructed and finely annotated for training and testing of the infrared ship semantic segmentation network. Through design experiments, SAPN can effectively deal with complex scenes. On the test set of infrared ship target semantic segmentation dataset, the mIoU of the model in this paper is improved to 70.26%, and it is better than other state-of-the-art networks. SAPN aims to effectively utilize the whole image information, not limited to a single target area. It can use all the information of the image as an auxiliary criterion for ship target recognition, and can provide an information basis for future intelligent decision-making and mission planning.

This paper designs a new platform for medical image transfer and process. The hardware part of the platform is based on FPGA, USB and RS232. The software part is based on Windows platform, basing on MFC dialog application developed with C + + programming tools in Microsoft Visual Studio 2010. The platform collects images from medical devices and uses the hardware platform to transmit them to PC for display, the application program on PC can realize the image data process and analysis.

As an important means of anti-ballistic missile weapons ,it is used for early detection of missiles, determination of missile parameters, determination of targets to be attacked by missiles, and provides advance warning for national strategic defence decisions. It plays an important role in ballistic missile defence system. The early warning satellites located in space are not limited by the curvature of the earth, they are condescending and have a wide coverage area, which can detect ballistic missiles moving in space early. Multi-band joint early warning has become an important development trend of space-based early warning. Space-based ultraviolet early warning is an effective early warning means that uses the ultraviolet radiation of missiles to detect missile targets in the active phase and re-entry phase. Based on the normalized detection rate, this paper deduces the formula for calculating the detection distance according to the sensitivity of the UV detector, and simulates the relationship between the system aperture and the detection distance ,as well as the relationship between the detection signal-to-noise ratio and the target temperature .The simulation results show that the system aperture of 50mm can meet the requirement of the signal-to-noise ratio of 6. With the increase of the target temperature ,the signal-to-noise ratio increases rapidly. According to the simulation results, a geostationary orbit space-based ultraviolet early warning system scheme is designed. The optical system adopts the off-axis total reflection type, and the working spectrum is 200~300nm, 220~290nm, 230~280nm, 255~275nm. For the spectrum segment ,four 9°×9° fields of view are spliced to achieve the requirement that the system’s field of view is not less than 18°×18°, ensuring global and earth limb coverage. Four cameras achieve full field of view coverage. Filters with different spectral are placed in front of the focal plane of each camera. The filters are installed on the filter wheel and driven by a motor to realize real-time monitoring of the world and obtain different spectral bands. Sections of experimental date to support background and target characterization studies. The structure design of this scheme is novel and has certain reference significance.

Dual-band IR detector can obtain infrared radiation information of two bands at the same time, which has many advantages compared with single-band detector in application. At present, there are two types of dual-band detectors: one is that pixels of the two bands align perfectly, and the other is that pixels of the two bands do not align perfectly, resulting in spatial inconsistency. The spatial inconsistency dual-band detector has the advantages of perfect temporal consistency and no need for deep mesa etching, but needs more complex image fusion processing to utilize its advantages. On one hand, the difference between images of two bands contains both spatial and band differences, which makes it more difficult to accurately use band information. On the other hand, pixels of the two bands do not align perfectly, which means that higher frequency spatial information can be collected, taking advantage of these information is conducive to improving the resolution of the image. In this paper, an image fusion framework is proposed. Firstly, band differences and spatial differences are separated and reconstructed, and then the band differences are enhanced by pseudo-color fusion algorithm. Through moving a spatial consistency detector with sub-pixel displacement, we get images to verify ours fusion scheme. Experimental results show that the proposed fusion algorithm can extract and enhance the band difference information, and improve the resolution of high frequency spatial information.

Pedestrian target tracking based on the UAV platform can be widely used in traffic control, field search, and military reconnaissance. It is an important research task of computer vision and intelligent cruise. Aiming at the limitations of the UAV surveillance system in moving pedestrian target tracking, such as background change, pedestrian deformation, occlusion interference, and lack of real-time performance, the dual Kalman filter is used to improve the traditional TLD tracking algorithm, the proposed method can accelerate the correction of the predicted detection area, reduce the disturbance of the environment background and the target deformation to the pedestrian tracking accuracy, and reduce the detection time by using the adaptive adjustment method of the detection area to offset the time cost caused by double Kalman filtering, to improve the Algorithm’s real-time performance. The test results show that the proposed method has high accuracy, stability, and real-time performance in pedestrian target tracking based on the UAV platform.

Because of its imaging characteristics, large field of view infrared images have low resolution and few high-frequency details. And it is difficult to obtain high-resolution large field of view infrared images as training sample database. Therefore, some super-resolution reconstruction algorithms that achieve better results in visible images may not be suitable for large field of view infrared images. Based on Convolutional Auto-encoders, a shallow Convolutional Auto-encoders which consists of four convolution layers, one maxpooling layer and one upsampling layer was constructed. And deep Convolutional Auto-encoders composed of 10 convolution layers, 2 maxpooling layers and 2 upsampling layers was provided. shallow Residual Convolutional Auto-encoders and deep Residual Convolutional Auto-encoders also were concluded. In order to make up for the shortcomings of large field of view infrared images, this paper adopts the combination of some large field of view infrared images and ordinary field of view infrared images as the image training library, and uses the large field of view infrared image data as the test set. The reconstructed image quality and the objective indexes of MSE, PNSR and SSIM show that the reconstruction effect of the shallow Residual Convolutional Auto-encoders is slightly better than that of the deep Residual Convolutional Auto-encoders, while the shallow s Convolutional Auto-encoders and the deep Convolutional Auto-encoders without residual model are not good. However, the reconstruction effect of deep Convolutional Auto-encoders is the worst due to the loss of more shallow information.

The simultaneous imaging polarization camera (SIPC) is an instrument for simultaneous polarization measurement using a three-beam splitter prism. Due to the large number of polarizing devices in the SIPC, the parameters and responses of the polarizing devices are different, which causes the measurement matrix of the instrument to deviate from the ideal value. In order to ensure the polarization measurement accuracy of the SIPC, effective polarization calibration is required. In this paper, a standard linearly polarized light source is used to calibrate the SIPC. Firstly, the measurement matrix of the instrument is calibrated by using the linear polarization calibration source, and then the calibration parameters are obtained by fitting Fourier coefficients with least squares. Finally, the polarization measurement accuracy of the SIPC is verified by calibration experiments. The results show that the polarization measurement accuracy of the SIPC is better than 4% after polarization calibration.

The blind pixels and the flash pixels of infrared detector, which are easily to be detected as the target, increase the false alarm rate. An algorithm about the detection of blind pixel and flash pixel is proposed in this paper. This method is based on the characteristics that the gray values of the blind pixels in the sequence images are basically unchanged, there is a jump in the gray values of the flash pixels, and there are obvious differences between blind pixels and neighboring pixels in spatial domain, the method of joint processing in space-time domain is used to detect blind pixels. Compared with the traditional algorithm, this method effectively avoids the problem of target signal suppression in blind flash pixel detection. The experiment of a 0.3m telescope shows that this algorithm can effectively eliminate blind flash pixels in infrared images. In the experiment of dim target detection, combined with multi-frame energy accumulation algorithm, this algorithm has the ability to detect targets with signal to noise ratio (SNR) ≤ 1 and the brightness of 10.8mVisdetected, which lays a technical foundation for the follow-up ground-based optical telescope to carry out full-time detection.

The optical target reconnaissance attitude, that is, the optical axis pointing of photographic or detection equipment, is an important parameter for active laser detection systems. A new recognition method aimed at optical target reconnaissance attitude based on active coherent laser beams is presented. Using the cat's eye effect of reflected light from active coherent beams scanning through an optical target along two orthogonal directions, optical target reconnaissance attitude can be calculated by measuring the edge peak amplitude ratio of the two reflected light time distribution envelopes. The usability of this method is validated through theoretical analysis and experiment. The results show that the theoretical minimum relative error of the recognition method is ⪅1%. The greater the deflection angle is, the smaller the mean of the relative error, the required fringe spacing for the minimum relative error are and the smaller influence of detection distance on relative error, therefore the more accurate the estimation will be. This method can improve the parameter identification ability of existing active laser detection and recognition systems, and it has important practical significance in judging the area of reconnaissance and tracking of optical targets.

In order to solve the problem that ground-based optical telescope cannot detect space targets in the daytime, an infrared detection method is proposed in this paper. Firstly, from the perspective of spectral characteristics of space targets and skylight, the short-wave infrared band (SWIR) of 0.9~1.7μm is optimized, which reduces the brightness of the skylight, and avoids the cooling of the optical system. Secondly, the signal-to-noise ratio (SNR) of the target is improved by the time-domain multi-frame accumulation algorithm and the goal of daytime 'extended range' detection of optical telescope is achieved. Experiments on a 0.3-meter telescope show that the space targets, which SNR less than 1 are detected by adopting this method in the daytime, when the zenith angle of sun is 40°, exposure time is 40ms, and the number of the cumulative frames is 360, the limit detection ability is 10.8mV. The results of the experiments well verify the theoretical analysis, which provides a reference for the system design of the next generation of ground-based optical telescope.

Infrared imaging detection technology has been widely used. In the process of using infrared images for target observation, a large amount of typical target infrared radiation characteristic data is needed as infrared reference information to eliminate interference factors such as environment, time period, and false targets to achieve accurate target identification. The acquisition of typical target infrared radiation characteristic data is to use infrared characteristic measurement equipment to accurately measure the measured target under various external environments and conditions, and finally form the available target infrared radiation characteristic data through data analysis and arrangement. Since infrared target characteristic data needs to be acquired in the field, these devices generally have the characteristics of working environment in the field environment, multiple types of measurement targets, long measurement distance and wide measurement space. Therefore, in order to eliminate the influence of external environmental factors and accurately obtain the infrared characteristics of the target, it is necessary to calibrate the key parameters of the large-aperture infrared characteristics measurement equipment on the test site. However, there is currently no field calibration capability for large-aperture infrared characteristic measurement equipment, which has a negative impact on the application of infrared imaging detection systems. In order to solve the above problems, this paper develops a large-aperture long-focus optical system in an external field environment, which mainly includes a high-temperature standard infrared radiation source, a large-aperture off-axis primary mirror, a secondary mirror, and a target. After the development was completed, it was applied in the external field environment to calibrate a certain high-resolution infrared characteristic measurement equipment, and the relevant data were analyzed. The analysis results show that the uniformity measurement uncertainty is better than 0.4K (k=2), the distortion measurement uncertainty is better than 1% (k=2). And a good application effect is achieved.

The curved CMOS bends its edge area for a better edge illuminance which effectively corrects the field curvature and image aberration as well as simplifies the optical system. In this paper, a full frame 24-megapixel camera lens of f=50mm and F#/1.8 with five pieces of ordinary glasses is designed by Zemax, introducing the curved CMOS and three aspherical surfaces into the design. The system uses a full frame (36mm*24mm) curved surface sensor with a viewing angle of 46°, an effective focal length of 50mm, and a total length of 82.5mm. The full viewing field MTF is greater than 0.4, the maximum distortion is less than 3% and the relative illumination is greater than 0.75. All of these optical results enable not only an excellent imaging quality but a simplified system with the introduction of the curved sensor.

The stray light is one of the main factors affecting the imaging quality of optical remote sensor. The design and experimental verification of stray light suppression is also the key link in the design of aerospace optical remote sensor. This article based on the development needs of aerospace cameras in orbit, the stray light suppression analysis and product assurance of imaging remote sensing cameras with RC configuration as the optical system (or main optical system) were studied in a quantitative way. First of all, the stay light characteristics of such cameras were revealed in a quantitative way, the design and addition of the optimal stray light suppression structures were completed, and comprehensive simulation verification was carried out through the light path tracking method. Secondly, in the design stage, in strict accordance with the control requirements of the development of aerospace remote sensing camera, the necessary and reasonable product guarantee control point is set up by PDCA cycle method. Finally, through laboratory stray light qualitative tasting and on-orbit verification, the full-link verification of camera stray light suppression is completed. This paper can provide a reference for stray light suppression design and process quality control of large-caliber optical remote sensors.

When the position and attitude of the moving platform change, the Los stability control technology can isolate the vibration of the moving platform, compensate the attitude change of the moving platform, ensure the stability of the front LOS, and realize the stable pointing in a specific direction and the scanning of the stable area in a specific direction. In the conventional system, the inertial navigation feedback loop is used to realize the self closing loop to suppress the carrier disturbance, but its disadvantage is that the application scenario is limited. We introduce inertial navigation into the control system for feedforward use, which requires bandwidth matching in the control method and stable loop in the control strategy. Aiming at this technical difficulty, this paper studies the Los stability control technology under the moving platform. Firstly, the working principle of LOS stabilization system is analyzed, then the control algorithm is modeled, and the position loop, velocity loop and acceleration loop are designed respectively. Then the LOS stabilization coordinate conversion model is established, and the conversion relationship from spatial coordinate system to moving platform coordinate system is obtained. On the basis of moving platform stability correction, encoder and inertial navigation are used to form a double closed loop to improve the control effect of LOS stabilization and to achieve the purpose of suppressing visual

A certain model should be used to predict and track the space objects that may affect the operation of satellites. In this paper, the Two-Line Elements (TLE) and the Simplified General Perturbations 4 (SGP4) models are used to calculate the position and velocity vectors of satellite A/B in the True Equator Mean Equinox (TEME) coordinate system and the Earth-Centered Inertial (ECI) system. Satellite A is selected as the observation platform to carry the camera, and the imaging positions of target satellite B on the camera of satellite A in the TEME and ECI coordinate systems are calculated respectively. The imaging trajectories are superimposed to generate several turns. The difference between the imaging positions in TEME and ECI coordinate systems is calculated, and the influence of the Earth's precession and nutation on the imaging trajectory is analyzed.

Aiming at the visual measurement requirements of space manipulators for grasping non-cooperative targets, a space target docking ring recognition and center point positioning method based on Tiny Darknet YOLOv3 fusion CenterNet is proposed. First, training network model based on open source ImageNet VOC 2007 and self-built spatial non-cooperative target data set and use optimized Tiny Darknet YOLOv3 fusion CenterNet deep learning algorithm to identify space target docking and obtain two-dimensional pixel coordinates of the docking center point; secondly, using the EnsensoN10-408-18 depth camera to obtain the 3*3 neighborhood data of the depth value corresponding to the center point and calculate the neighborhood weighted optimal value to get docking center spatial coordinates in the camera coordinate system. Combined with the hand-eye calibration relationship, the docking center spatial coordinates are converted to the UR5 manipulator base coordinate system. A ground verification system for manipulator to capture the target was built to test the target docking ring identification and center point positioning, and the accuracy error evaluation is completed based on the OptiTrack motion capture global measurement benchmark system. The experimental results show that target positioning accuracy is better than 10mm, and real-time data update rate is better than 2Hz in the dynamic approximation process from 1.5m to 0.2m, which can effectively solve the slow speed and poor accuracy caused by the influence of environmental lighting, target surface material, target attitude scale changes and other factors in traditional feature extraction methods. It lays a foundation for the safe arrival, capture and other manipulator fine operations.

Temporal phase-shifting interferometry (TPSI) has been proposed for morphology monitoring of Plasma-Facing materials (PFMs) in Tokamak due to its high precision and far-field online capability. However, this monitoring method is sensitive to vibrational environment and the mechanical vibration in Tokamak, such as the Experimental Advanced Superconducting Tokamak (EAST), would lead to a decrease in the accuracy of the measurement or even wrong results. Real-time detection of the vibration parameters of the Tokamak during the plasma operation to compensate for the error of the TPSI measurement is a solution to improve the accuracy. In this paper, a laser interferometry platform for diagnosing and measuring vibration amplitude and frequency adopting the fringe-counting (FC) method has been introduced. We measured the different vibration amplitudes and frequencies using the proposed approach. The results show that the method has a potential application for in-situ measurement of surface morphology of PFMs in Tokamak like EAST.

In recent years, the snapshot multi-dimensional imaging technology is emerging and becomes an increasing research focus. Especially, the spatial, spectral and depth information of scenes is particularly useful in target detection, recognition, tracking, scene classification et al. This paper proposes a snapshot compressed light field imaging spectrometer based on compressed sensing with light field concept and a snapshot depth-spectral imaging architecture based on image mapping and light field to realize the capture of depth-spectral information simultaneously. Through simulations, we demonstrate that the proposed snapshot depth–spectral imaging systems are effective to measure the depth-spectral information of scenes in a single snapshot time.

To measure flame temperatures in various complex and extreme environments, we propose a two-dimensional flame temperature measurement method based on infrared radiation. In the laboratory environment, the acetylene-oxygen premixed flame was generated by a simulated flame generation device, the two-dimensional infrared image of the flame was obtained by using a cooled infrared thermal imager, and the emissivity of the acetylene-oxygen flame was obtained by combining a colorimetric pyrometer, the atmospheric transmittance of the site is measured by using an atmospheric correction factor, a flame radiation decay transmission model was established, and the temperature calibration curve of the infrared thermal imager was combined to finally obtain two-dimensional flame temperature data. Through the temperature measurement uncertainty analysis, the temperature measurement error of the system is within 5%. The experimental results validate the feasibility of the method.

When capturing images, traditional imaging devices can only record images with low dynamic range (LDR) and cannot capture scene information with high dynamic range (HDR) in the real world due to their own response characteristics. Therefore, high dynamic range imaging technology has developed rapidly and gradually become a research hotspot in the field of digital image processing. The main problems of current multi-exposure images to generate HDR images include ghosting caused by camera shake and foreground objects moving, and information loss in overexposure and underexposure situations. To solve the ghost problem, the gradient direction histogram descriptor is used to process multi exposure images, and the brightness invariant motion estimation technology based on feature optical flow is used to generate high dynamic range images. The algorithm first selects the well exposed image as the reference image, and uses the gradient direction histogram descriptor which is robust to the illumination change to process the images with different exposure times, then uses the optical flow estimation algorithm to distort the input image to the reference image according to the corresponding relationship between image features ,finally synthesizes the final HDR image according to the weight map .The experimental results show that compared with the existing HDR algorithms, the proposed method has a certain improvement in performance.

Back projection (BP) algorithm is widely used for ground penetrating radar (GPR) imaging of layered scenes. Considering the inevitable refraction phenomenon in the layered scenes, the BP algorithm necessitates repeatedly solving quartic equations all over the imaging scene to determine the positions of refraction points. However, the existing algorithms calculate the quartic equation of the refraction point through iterative approximations, especially when the relative permittivity of the scene gradually increases. These algorithms rely on the manual setting of the iteration threshold and are time consuming. Therefore, this paper proposes a BP algorithm based on linear estimation of refraction point position (LERP) for the layered scene with decreasing permittivity. We propose a two-step LERP algorithm that rewrites the quartic equation of the refraction point and directly estimates the refraction point position. The LERP algorithm consists of the coarse estimation inspired by the scene features and the precise estimation guaranteed by the quartic equation. The LERP algorithm reduces the quartic equation to a linear algebraic form. Following this, the LERP-based BP algorithm promotes efficient imaging in the case of decreasing permittivity. Comprehensive experiments verify that the proposed LERP algorithm meets the resolution requirements of GPR exploration. Compared with the existing algorithms, the proposed algorithm avoids manually setting iteration thresholds, and improves the efficiency of estimating refraction point positions and thus the BP algorithm.

The FPGA+DSP architecture has been widely used in spaceborne digital signal systems. In order to adapt to the complex space environment, reduce the impact of single-event flipping, and meet the on-orbit requirements of intelligence and high reliability, a spaceborne dual-core system is proposed. On-track betting method. Taking Fudan Micro JFM7 series JFM7K325T and TI's TMS320C6678 as examples, the hardware circuit design and software design of FPGA+DSP program on-rail injection are introduced in detail. The ground experiment verification proves that the on-rail injection method is reasonable and feasible, and improves the reliability of the system that can complete the remote fault repair and function expansion of the onboard software.

It is an important and challenging topic to deal with infrared small target detection with high detection rate, low false alarm rate and low computational complexity in various application fields. Aiming at solving the problem that the existing algorithms can not effectively enhance the real foreground target and suppress various complex background interference. This paper proposes an infrared small target detection algorithm based on entropy weighted multiscale local contrast. Firstly, the local contrast formula is redefined in the joint form of ratio and difference, which can enhance the target and suppress the background clutter. Secondly, the local entropy can be used to reflect the gray mutation in the local area of the image. We use the modified local entropy operator to weight the multiscale local contrast. Finally, we employ the adaptive threshold segmentation to separate the target from the background and obtain the final infrared small target. We test six groups of infrared image sequences with different targets and backgrounds, the backgrounds include mountain, forest, field, sea-sky, sky and thick cloud. Experimental results show that, the proposed algorithm can not only robustly detect infrared dim and small targets of different sizes in various complex backgrounds, but also has higher detection efficiency and lower false alarm rate compared with other traditional baseline methods.

Remote sensing images obtained from a single sensor have the disadvantage of incomplete information in terms of either low spatial resolutions or low spectral resolutions. To overcome this disadvantage, a pansharpening algorithm based on weighted mean curvature filtering (WMCF) and dual-channel pulse-coupled neural network (PCNN) in multi-scale morphological gradient (MSMG) domain is proposed in this paper. Firstly, the PAN image is decomposed into three parts, a small-scale image, a large-scale image, and a base image through a WMCF-based decomposition model. Then, a PCNN fusion strategy modulated by MSMG is used to fuse the base image and each band of the MS image. Finally, each fused bands are combined to obtain the final fused image. Experiments in four datasets demonstrate that the proposed algorithm obtains the best performance in most cases.

One of the key technologies of high precision star sensor is to improve the star location accuracy of star sensor, which plays an important role in astronomical navigation. Because the traditional star location algorithm is based on the standard Gaussian distribution model, the location accuracy is poor when the star energy is not Gaussian distribution. According to the different imaging models of stars by star sensors, a subpixel localization algorithm based on iterative Lagrange interpolation is proposed to improve the centroid extraction accuracy of non-Gaussian stars. Experimental results show that the accuracy of the proposed method is up to 0.01pixel, and the average error of the proposed method is 49.38% higher than that of the traditional method.

Aiming at the increasing demand of space dim and weak target detection camera and meeting the demand of small size and light weight, this paper proposes the design and implementation of a light and small low light level camera based on FPGA. The camera adopts IMX253, a high resolution and high response CMOS image sensor produced by SONY. FPGA is used to receive the data output by the sensor, cached in DDR3, and then transmitted to the data transmission system through TLK2711 interface. This paper introduces the camera system scheme, hardware design and camera driver with FPGA as the control core. Verilog hardware language is used to realize IMX253 timing drive, image acquisition, DDR3 data cache and TLK2711 interface communication. The imaging experiment of the system is carried out. The results show that the camera system runs stably, has high imaging quality and strong detection ability. The camera image resolution is 2048*2048, quantization bit is 12bit, frame rate can reach 20Hz. This system provides effective image data for space weak target detection.

fDSST (fast Discriminative Scale Space Tracking) belongs to the correlation filter tracking algorithm, which has a high success rate and precision, and also runs at a fast speed. However, it is still a huge challenge for the tracking scene of fast motion and similar object interference. In order to improve the performance of fDSST on the challenges above, this paper proposed the fDSSTs algorithm and the fDSSTss algorithm respectively. fDSSTs increases the response scores near the object location by fusing the fhog feature and the color statistical feature, so improved the tracking performance of fDSST in the fast moving scene. fDSSTss adds a multi-feature object association module on the basis of fDSST, which distinguishes the real object and the interference object from the object feature level, thereby maintaining the tracking of the real object. The fDSSTs is tested on the OTB50 dataset, in fast-moving scenarios, the success rate of fDSST is improved by 20.5% and the precision is improved by 22.8% compared with fDSST. The fDSSTss is tested on the test sequences of similar object interference, and the result shows that fDSSTss has better anti-similar object interference ability than fDSST, while meeting the real-time requirements. The experiments show that the improvements improve the success rate and precision of fDSST in fast object moving scenes, as well as the ability to resist similar object interference.

In this paper, the optical design and evaluation of the large field of view infrared imaging system are first carried out based on new optical components such as free-form surface. And the aluminum alloy material is selected as the optical substrate material, and the optical machine design is performed based on the design idea of structural function integration. In the last the mechanical properties and thermal stability of the optical-mechanical structure of the system are analyzed to explore the environmental adaptability of the system.

In order to meet the needs of border reconnaissance and surveillance tasks, improve the detection capability of moving target detection for vehicles, people and unmanned aerial vehicles in unattended environment. In this paper, a mechanism of photoelectric reconnaissance in unattended environment is proposed, which can realize the functions of space three-dimensional sector scanning reconnaissance, target detection, threat warning and so on. The technologies of area coverage, moving target detection and target false alarm involved in the mechanism are analyzed one by one. The coverage strategy of sector scan area suitable for unattended operation, the optimized moving target detection algorithm and the adaptive adjustment technology of optical field of view for targets with different characteristics are proposed. The experimental results show that the system can effectively detect the target with the above characteristics, improve the detection probability of the target and the accuracy of threat warning, and provide strong support for unattended environment.

For the scientific complementary metal-oxide-semiconductor detector with dual gain control function, two images can be output simultaneously at the any exposure time. The low gain image has small pixel brightness value, and most of low illumination regions are usually black pixel. However, the high illumination regions in the high gain image may be saturated and overexposed. To obtain a detailed image for different illumination, a high dynamic range image fusion method base on dual gain grayscale image was developed. First Laplacian pyramid for dual gain images was established; then fusion was performed according to the weight value of each layer and image reconstruction was carried out by the pyramid results. Finally, the high dynamic range image could be obtained through grayscale adjustment. Results showed that the high dynamic range image fusion had better performance than others in many regions, such as the buildings, the roof, the sky and cars with low illumination. The image still had high resolution under the condition of zoom. Therefore, the fusion method base on dual gain grayscale image is suitable to high and low gain image, and it provides reference for high dynamic range image generation.

The target detection ability of external thermal imaging system is affected by many factors, including the source and influence of system heterogeneity, the digital enhancement mechanism of infrared imaging, the realizability and real-time of system super-resolution and so on. The infrared focal plane detector integrates focal plane daylighting array, signal readout circuit, temperature control circuit, timing control circuit, etc. requires the external supply of appropriate driving voltage and digital timing signal to work normally. Because the infrared detector belongs to the front-end device of the system with high sensitivity, its requirements for working voltage and digital timing are also relatively strict. The quality of driving signal determines whether the infrared detector can work in the best state, so that the following image processing circuit can get the best original infrared image. By studying the imaging principle of uncooled focal plane detector, this paper puts forward the key factors affecting the performance of infrared image, and puts forward hardware based low-noise bias voltage signal generation technology, which improves the intelligent level of the system under the condition of ensuring the stability of the system.

Asteroid detection radar provides scientific data support for inversion of internal address structure and material composition by obtaining the reflection echo of strange medium on the surface and inside of the star. The detection method of asteroid companion determines that radar system can’t extract target echo form strong surface clutter without Doppler information in the detection process. At the same time, compared with Mars radar detection, resource constraints are more stringent, and the resolution are required higher. In this paper, a multi-point and multi-angle long time stepped frequency broadband synthetic detection scheme is creatively proposed, which effectively solves the contradiction between penetration depth and resolution, the SNR is not enough of sigle-pluse, and the extraction of target echo form strong clutter, etc., providing theoretical basis for the design of asteroid detection radar system.

Target tracking and location based on azimuth measurement only is a kind of method to estimate the position, velocity and other motion states of the motion target, which works by using the noisy azimuth information of electromagnetic wave or acoustic signal passively received by the sensor. Because of the outstanding advantages of simple principle and good concealment, it is widely used in photoelectric reconnaissance and countermeasure. In order to realize the tracking and location of moving targets by ground observation stations, the target motion model is established based on the plane rectangular coordinate system, and the target state is estimated by the least square method. Several main factors determining the accuracy of target tracking and location are analyzed, and the mean and standard deviation of location error are simulated and analyzed by Monte Carlo method. The effects of the number of observation stations, target distance and angle measurement accuracy on the location error and its distribution law are revealed. The simulation results can be used to evaluate the location effectiveness of moving targets, effectively improve the location accuracy of targets and optimize the parameter configuration of observation stations.

In the unmanned photoelectric reconnaissance vehicle network, each node cooperates to locate the target, which is beneficial to expand the reconnaissance range and obtain the target position information covertly. The unmanned photoelectric reconnaissance vehicle of each node can provide the angle information relative to the target when it reconnoitres the target. How to use the angle information of the target detected by each node to obtain the estimation of the target position information is worth studying. This paper studies the passive positioning technology in the unmanned photoelectric reconnaissance vehicle network, establishes the model of the unmanned photoelectric reconnaissance vehicle network for cooperative target positioning, and uses the least-squares method to design the target positioning algorithm. The error between the target position value and the true value is within 10m, which proves that the algorithm can effectively obtain the target position information, and provides an effective method for the hidden acquisition of target position information in the unmanned photoelectric reconnaissance vehicle network.

This paper designs an image processing platform suitable for spaceborne equipment with FPGA and DSP as the core. In this paper, the hardware architecture, the selection of key components, and the interaction design of the interface between FPGA and DSP are introduced in detail. During the experiment, six high-definition cameras were used to capture multiple images of the visual target fixed in the motion mechanism, and the function and performance of the system were fully tested. The results show that the platform has the ability to receive image data from six high-definition cameras at the same time while only consuming 18w of power. And within 0.5s, based on the image data of the visual target captured by the six cameras, after image preprocessing, image noise reduction, threshold segmentation and other related processing, the relevant pose information is solved, the position error is less than 1mm, and the attitude error is less than 0.1°, the platform has high computing precision, fast computing speed, good stability and low power consumption.

The work concerning the laser-induced damage under long-range (km-class) outdoor testing is very limited due to the difficult, laborious and time-consuming process. In this paper, we demonstrate a 1.5 km outdoor experiment of observing the laser-induced damage of CMOS imaging sensor and predicting the required pulse energy at other propagation lengths and visibility conditions theoretically. The outdoor experiment verifies that large amount of pixel permanent damage on a commercial visible-band CMOS camera can be produced by using the 532 nm pulsed laser with an output energy of higher than 50 mJ at a propagation range of 1.5 km and the atmospheric visibility of 10km. Meanwhile, the laser power density travelling through turbulent atmosphere is estimated theoretically by using a phase screen model. The required laser energy to damage the sensor for different propagation length or visibility condition could be predicted. The simulation results indicates that the atmospheric effects lead to significant impact to the spatial profile of laser beams at long propagation range, which should be considered and analyzed delicately when one is designing a laser countermeasure device.

Aiming at the problems of small size and complex background of infrared targets detected at long distances in airborne aerial scenes, the average recognition rate is low, and the real-time performance of the airborne infrared target recognition algorithm is high. In this paper, an improved EfficientDet infrared small target recognition algorithm was proposed. First, an Unsharp Masking method suitable for small infrared target data enhancement is used to enhance the target edge and detail information; Secondly, GhostNet was used as the backbone network of the model, which greatly reduces the amount of parameters of the model and improved the inference speed of the model; Finally, the Coordinate Attention module was used. It was applied to the feature layer extracted by the feature extraction network, which increased the feature expression ability of the network and prompted the network to accurately capture the position information of the small infrared target. The experimental results show that the average accuracy of the optimized algorithm in pure background, complex background, small-scale target and multi-target application scenarios is improved by 2.24%, and the FPS reaches 46.56. Small target recognition provides the basis for edge computing.

In order to remove or at least significantly reduce the interference caused by incident laser, the detection for the laser spot in infrared image is indispensable. According to the shape and gray distribution characteristics of laser spots, the laser spot is identified and located in the infrared image by using the SIFT feature matching algorithm. In order to verify the effectiveness of this method, interference laser irradiation experiments with different laser powers are carried out. The experimental results show that this method can accurately detect laser spots in infrared images, and can adapt to different sizes of laser spots.

To study the temperature distribution of the methane combustion process, the methane and air premixing model was simulated using fluent fluid simulation software, and the distribution clouds of temperature and H2O molecules were given. And the combustion region at 5 cm high was selected to study the relationship between the temperature and the mass fraction of H2O. Meanwhile, according to the principle of temperature measurement by TDLAS technology, the gas temperature was simulated in SIMULINK, the absorption line of H2O molecules was selected as the temperature measurement spectral line, and the spectral absorption model was established using the HITRAN database, and the flow chart of the simulation platform construction was given, including the light source module, gas chamber module, and data detection module. Under certain conditions, the temperature simulation data were obtained by giving 15 groups of H2O mass fractions. The results showed that the temperature measured by the TDLAS system was consistent with the temperature simulated by Fluent software, and the error range was within 5%.

As far as resolution is concerned, a system with pixels exceeding 4K (3980*2040) or 8K (7680*4320) is called Ultra HD. In this paper, to fill the gap in UHD testing and evaluation, we take a full frame 8K HDR camera equipped with a zoom lens as an example, evaluating the system performance by a comprehensive test. Next, according to the results, a new testing process including three indicators with corresponding criteria is designed to make a supplement to BT.2020 criterion and offers an integrated test for 8K camera lenses.

To precisely calculate geometric parameters of space-borne optical imaging systems, such as object distance, projection angle, ground sampling distance (GSD), swath width, the effect of earth curvature and projection angle, these imaging systems are researched as nadir imaging and roll imaging. In this paper, a precise geometric model is proposed, which is based on earth curvature and projection angle. Two types of space-borne optical imaging systems are simulated by the model. They are single camera and combined camera with large field of view (FOV). They are on 644.5km orbit, with full field of view 64.44°. The analysis shows that, the GSD of combined camera changes rapidly with field angle, the maximum GSD is 2.07 times of the minimum GSD. The GSD of single camera changes less rapidly with field angle, the maximum GSD is 1.75 times of the minimum GSD. The swath widths of sub-cameras of combined camera are different. The two marginal sub-cameras have larger swath width than the two central ones. Therefore precise calculation of geometric parameters is significative to ensure the imaging quality.

This paper builds a real-time infrared target detection system with a visual positioning function based on FPGA, a visual camera, and an infrared camera. Firstly, the whole system is built based on FPGA. The design and implementation of the infrared image acquisition module, a data storage module, SD card module, and image display module are completed. Ping pong operation is used for the data storage modules to realize video stream transmission. The experiment results show that the system built in this paper can collect and display the target in real-time. To improve the system performance, several image processing algorithms are proposed, including an improved median filtering algorithm, linear transformation, and Laplacian sharpening algorithm; a combined algorithm of histogram equalization, Gamma transform, and Laplacian sharpening; a target detection algorithm combined with threshold segmentation and a background difference algorithm; and a visual localization algorithm. Software simulation and FPGA hardware implementation results show the effectiveness of the proposed algorithms.

Although the traditional dehazing algorithm can improve the clarity of hazy weather images, it may lead to the loss of many details and the distortion of color saturation in the process of processing. In order to overcome this defect and enhance the details of the image, a single image dehazing algorithm based on non-subsampling contourlet transform was proposed. First, the captured fog images are mapped from RGB space to HSI space, and the luminance channel map and saturation channel map are processed separately. The luminance channel image is decomposed by non-subsampling contourlet. The obtained high-frequency components are filtered by a guided filter, which can smooth the image while maintaining the edge. The obtained low-frequency components are processed by the single-scale Retinex algorithm to enhance the details of hazy areas in the image. A new luminance channel image is obtained through certain fusion rules and the inverse transformation. Then, the degradation model of the saturation component map is established. The parameters are estimated using the dark channel prior principle, and the estimated saturation map is obtained. Finally, the new luminance channel image, the estimated saturation image and the original hue channel image are inversely transformed to RGB space, resulting in a dehazed image. Experiments show that the method in this paper can solve the problem of color distortion in bright areas to a certain extent and the color saturation of the image, while keeping the overall outline structure of the image clearly and the edge details prominent. The visibility of the whole image is also improved, which is prior to the traditional detection algorithms.

We have recently developed an actinic full-field EUV patterned mask inspection and review system on a tabletop by using a coherent high-harmonic generation (HHG) Extreme Ultra-violet (EUV) source. By adopting a combination of reflective-mode fly-scan scattering detecting and scanning coherent diffraction imaging methods, the actinic defects can be sensitively detected with high throughput and precisely reviewed with a finer resolution. In this work, we propose a model of a two-step EUV mask cross-scale inspection (EMCI) tactic for fast identification of actinic defects and high-resolution review of the EUV mask, which is based on difference analysis of diffracted intensities and precise ptychographic reconstruction of the EUV mask. The proposed EMCI model consists of two steps. In the first step, a fly-scan diffraction difference mapping (FDDM) method is applied to recognize and localize the defects from the EUV mask with full field of view. Thus, a sub-micron resolution defect location map is generated by array to array comparison of the diffracted intensities from the line integral of scanning regions with programmed defects, to regions of defect-free. This FDDM method works particularly in Fourier domain with no need to any form of imaging system, meanwhile, scattering information takes the advantage of high sensitivity to nanoscale defects, so that defects can be recognized and localized with high throughput and robustness. In the second step, with the location information of defects by FDDM, an EUV Ptychography (EUVP) method is applied to do the local review of EUV mask by retrieving the image of both the EUV mask and illumination based on ptychography. In this manuscript, utilizing the proposed EMCI model, we have performed a numerical simulation for EUV patterned mask defect inspection and review. The results reveal the performance of the proposed model in EUV mask metrology. The proposed method is particularly expected to have a remarkable implication for the EUV lithography.

Microlens arrays are composed of sub-lenses with dimension of a few tens micrometers. They have the advantages of compact configuration, high integration, unique imaging characteristics, and easy replication in batches. They are gradually emerging in naked-eye display technology. This paper discusses the principle and technique of an anti-counterfeiting label based on a microlens array. Mohr Nanotech 650FG ultra-precision five-axis CNC machine is used to process the microlens arrayed copper master mold and the nickel mold is fabricated by electroplating process. Then the 400-line micro-lens array PC film is produced by the hot embossing process. Finally, by integrating the PC film with the anti-counterfeiting micropattern the function of the anti-counterfeiting label based on microlens array was experimentally verified.

To promote the super-resolution (SR) technology in real-world applications, the blind SR, involving kernel estimation and image restoration to super-resolve images with unknown degradation, has become one of the research focuses. Most existing methods either implement the above two tasks step-by-step so that do not well consider the compatibility between them, or repeatedly apply two modules over and over again to emphasize cooperation but limit the adaptive development of each one. Towards the above issues, based on the Deep Alternating Network (DAN), a novel training strategy named switching the iteration is proposed in this paper. In the first stage, an estimation module and a restoration module are optimized alternately to promote compatibility. In the second stage, duplicate the pre-trained modules and place them alternately to form a linear structure to promote adaptive development. Extensive experiments on isotropic Gaussian degradation datasets and irregular blur kernel degradation datasets show that the proposed method can achieve visually pleasing results and state-of-the-art performance in blind SR.

As the need for image resolution, transmission rate, and integration rises in space remote sensing applications, the charge accumulation-based TDI-CMOS sensor devices evolve fast. This study proposes a TDI-CMOS imaging system based on FPGA to answer the challenge of high-resolution, wide-format multispectral imaging. First, the device selection and stitching design ideas are clarified based on the index requirements of the imaging system; second, the design techniques of the TDI-CMOS imaging system are emphasized, and the implementation methods of critical technologies such as TDI-CMOS timing drive, register configuration, P-spectrum, and B-spectrum image data training, and high-speed data interface design of the imaging system are illustrated; third, the relevant experimental work is described. In conclusion, the experimental work is described, and the experimental findings are examined and interpreted. The experimental findings demonstrate that the imaging system has a signal-to-noise ratio of 45 dB for P-spectrum and 55 dB for B-spectrum and that the resolution of picture elements is 8288 columns for P-spectrum and 2072 columns for B-spectrum.

An optical apparatus was proposed in this paper that allows simultaneously equal-optical-path imaging of both front and rear end surfaces of the thermoelectric cooler (TEC) components. This optical apparatus can be used to simultaneously inspect surface defects on both front and rear end surfaces in the traveling direction of the TEC components. Two sets of right-angle relay prisms and one image combiner are used to build an optical apparatus for simultaneously equal-optical-path imaging of both front and rear end surfaces of TEC components. The experiments of defects inspecting both front and rear end surfaces of the TEC components were carried out. The inspecting apparatus was used to collect 10,000 images and the ResNet50 deep residual learning network was used to extract and learn its features. The accuracy of the trained model of 94.8% was obtained and the average inspection time for a single image was around 58ms. The experimental results show that the proposed optical inspecting apparatus can ensure the clear imaging of TEC components on both front and rear end surfaces on the CMOS sensor. It meets the requirements of TEC components end surface defects inspection and simplifies the system configuration, reduces the system cost, and improves the system reliability.

Cultural relics contain unique and rich historical, artistic, economic and other diversified values. However, the imitation and counterfeiting of cultural relics have brought great challenges to the protection and research of cultural relics. In order to improve the problems of strong subjectivity and low precision of the traditional "ophthalmic" identification method, this paper combines spectroscopy with cultural relics to identify the authenticity of pottery and porcelain cultural relics. Under constant temperature and humidity conditions, four kinds of LED with different spectral bands were used as experimental light sources, two Jingdezhen moon flower winter melon porcelain vases with the same appearance and two songxianghu kiln white glazed small clay pots with the same appearance were used as cultural relics samples, and multiple feature points were selected for precision spectral detection. Treat the detection results as multidimensional vectors, calculate the Euclidean distance, Manhattan distance and Chebyshev distance between the vectors, and look for the appropriate threshold to identify the authenticity of the artifact. The results show that: First, the spectral difference between the feature points of cultural relics with the same appearance is significant, and the source of cultural relics can be accurately identified by using the spectral curve; Secondly, this paper calculates the thresholds based on Euclidean distance, Manhattan distance and Chebyshev distance for porcelain and pottery. Among them, the accuracy of identifying porcelain using a threshold based on Euclidean distance is the highest, which is 87.5%; The accuracy of identifying pottery using a threshold based on Manhattan distance was the highest, at 91.67%. By using the spectral curves and thresholds of cultural relics measured by precision spectrometers, this paper generates the spectral identity card of cultural relics. Compared with traditional cultural relics detection, the spectral dimension can better meet the needs of archaeologists for in-depth research on cultural relics.

Intelligent harvesting is one of the important criteria to measure the development level of agricultural modernization. Coordinated operation of harvester-grain truck clusters can improve grain harvesting efficiency and reduce post-production losses during large-scale rice/wheat concentrated harvests. Overloading the grain on the grain truck will cause serious scattering of grain, further, insufficient loading can result in wasted capacity. How to monitor the grain loading process dynamically is a pressing matter. In this paper, two cameras and a point laser were used to measure the status of grains in the truck in real-time. The loadable capacity of the grain truck can be obtained through the reconstruction of the grain truck carriage edge and the positioning of the bottom of the truck carriage. During the harvester grain unloading process, the cone tip of the wheat pile is irradiated by the laser, and the height of the wheat pile can be obtained by measuring the location of the laser point. Then insufficient loading or overloading can be avoided by controlling the speed of the unloading port. This method has been verified in the paper box. The results show that the dual-camera monitoring system can measure the volume of the grain truck in real-time, and feedback on the total amount of grain loaded in the grain truck in time, which can effectively avoid grain loss caused by excessive loading.

Star sensor is the key measurement equipment for satellite positioning and spacecraft attitude control. It provides high-precision measurement data for spacecraft attitude control and astronomical navigation. In order to realize the accurate measurement of star positioning and spacecraft attitude by star sensor in the environment with large temperature difference in space, according to the thermal compensation theory, an athermal star sensor lens with wide band, large field of view, low distortion is designed, which can work in wide temperature range. The working band is 450nm to about 850nm, the F number is 1.5, the field angle is 20°, and the diameter of the pupil is 30mm. The analysis results show that the relative distortion of the system is less than 0.06%, the lateral aberration of the full field is less than 3.7μm, the surrounding full field-of-view energy ratio within φ20mm is large than 80%, and temperature range is -50℃ to about 60℃. The change of relative distortion, lateral aberration, energy concentration and other indicators relative to 20℃ is no more than ±10%, which fully meets the application requirements of high-precision star sensor in space environment.

Target acquisition task-oriented effectiveness evaluation methods for optical remote sensing systems are helpful in the design phase to quantitatively evaluate and predict the target detection ability of optical remote sensing systems. Compared with the widely-used National Imagery Interpretability Rating Scale (NIIRS) and Johnson criteria, the Targeting Task Performance (TTP) metric has a more comprehensive evaluation model for electro-optical imaging systems, combined with the target features and human eye functions. This paper discussed the effects of the image luminance and noise distribution on the target acquisition task, and proposed a revised TTP metric, aiming at improving the accuracy of the effectiveness evaluation model. Aerial remote sensing experiments were carried out, and the ability of an optical remote sensing system to detect and recognize the target models was evaluated based on the proposed method. For aerial images under the NIIRS levels ranged from 2.98 to 4.43. The detection and recognition probabilities of aircraft models were calculated using the original and revised TTP metrics, respectively. It is inferred that the evaluation results by the revised TTP metric are in better accordance with the NIIRS level of the images.

Due to the diffraction limit of optical system and detector fabrication technology, super-resolution imaging has been an important means to achieve high spatial resolution in remote sensing. One super-resolution imaging method based on sub-pixels is explored in the paper, the mechanism and image reconstruction of the method are mainly studied. Taking one remote sensor as a sample, registration accuracy of homonymous points, which matters to super-resolution image reconstruction, and its influencing factors, are analyzed, showing that, the image resolution can be improved about 1.5 times when the registration accuracy of homonymous points is better than 0.12 pixels.

Aiming at the problem of thread measurement with small pitch, a screw thread parameters measurement method based on machine vision is proposed, which solves the problem that the tip of the mechanical scanning probe is too large to measure the small size pitch diameter. This work developed a method of image processing method to detect the edge of screw thread parameters. The screw thread image is collected by calibrating the camera to correct the distortion error. Canny edge detection is used to detect the edge contours in the thread image, as well as mean filtering and median filtering. Gaussian smoothing filtering is also studied to obtain higher measurement accuracy: a sub-pixel subdivision technique is designed to improve the resolution of the imaging system. In order to rotate the screw thread image, a minimum rectangle fitting algorithm for the measurement area is developed. The affine transformation matrix is constructed by the center of the measurement area and the orientation of the long axis of the screw thread. This thread parameter edge detection technique has the advantages of simple and quick operation and high measurement accuracy.

Image registration is a typical problem and technical difficulty in the research field of image processing, which can be used in infrared image fusion, image Mosaic, image segmentation, super-resolution reconstruction and other directions. On the basis of infrared image registration, considering the difference of infrared image, the effective accuracy of registration is set. The algorithm in this paper was initially used in super-resolution reconstruction, but it was redesigned in the registration process due to the need to reduce the computing cost in hardware implementation. The algorithm is improved on the basis of the original flownetS, and the cost of the calculate is reduced by 89% when the number of convolutions layers and the receptive field of the improved network are the same. There is no need for pooling layer, because pooling provides greater receptive field while reducing resolution, which will lead to spatial information loss and data loss. Dilate convolution convolution can avoid down-sampling and provide a larger sense field under the premise of the same amount of computation. Set different Dilation rates, receptive fields will be different, and there will be multi-scale information. This method based on deep learning uses the processing method of dilated convolution to greatly reduce the cost of network computing and provide a convenient channel for the hardware implementation of the algorithm. Moreover, the algorithm also achieves excellent results on the development board RK3399Pro. Combined with infrared image, this paper also demonstrates the difference between infrared image in the registration of effective accuracy and visible light, and also analyzes the target at different speed, the minimum network structure required. Finally, an appropriate ratio was selected through experimental attempts to ensure stable accuracy in the conventional moving target.

Many sources of spectrometer system noise are introduced, which will be superimposed on the interference data. In this paper, the statistical properties of noise are analyzed, and Gaussian models are established by extracting features from the actual collected interferometric data. For 30-degree and 35-degree target radiation sources, the same sets of interferometric data are collected, and the histogram of noise is established and the curve is fitted to match the corresponding Gaussian model. The ideal interference fringe is simulated for the studied spectrometer object, and the effect of Gaussian noise on the interference fringe is analyzed, and the experiments prove that the effect of the noise-added interference fringe is close to that of the measured interference fringe.

Rotational Doppler effect (RDE), as a counterpart of the conventional linear Doppler effect in the rotating frame, has attracted increasing attention in recent years on rotational object detection. In practical applications, it is common to see the condition that the beam is obstructed or not fully illuminated on the object, especially in long-rang detection conditions. For example, the fan blades are always wrapped inside the frame, the rotors of engines are arranged inside the machine, to name a few. How to realize the rotational speed measurement when the OV cannot fully illuminate the rotating target is a significant issue for the application of the RDE metrology. However, the principle of the RDE of fragmental optical vortex (FOV) has not been investigated yet. Here, we investigate the RDE of the fragmental optical vortex for the first time. Based on the orbital angular momentum (OAM) mode expansion technique, we establish the relationship between the OAM spectrum and the RDE frequency shift of FOV. The mechanism of the rotational speed extraction is analyzed and validated by the numerical simulation and experiments. Further, a dual Fourier transformation method is proposed to accurately obtain the rotational speed which successfully overcome the problem of the discrete distribution of the RDE signals. Our work may be useful for practical remote sensing based on the optical RDE metrology.

Real time control, diversified functions, system integration and miniaturization are an important development direction of video electronics system. Embedded design based on FPGA can manage system resources more reasonably and effectively, and use limited resources to achieve more complex functions. It will become an important design method to promote the development of video electronics technology. Based on the embedded MicroBlaze microprocessor in V FPGA chip, combined with the model application background and Xilinx embedded development platform, an eight channel gray image channel inconsistency correction algorithm is implemented. On board experiments show the feasibility of applying embedded system to video electronic design, and show its advantages in interface control, storage management, process control, floating-point operation, development efficiency and so on, and it can be applied to real-time image processing of satellite remote sensing camera

Absolute distance measurement based on the dual-comb system is a promising tool for the large-scale measurement in the industrial field. There are two combs with slightly different repetition rates in the dual-comb system, and the distance information could be obtained by the asynchronous optical sampling (ASOPS). However, the measured range could be limited within the pulse-to-pulse interval range by the non-ambiguity range (NAR) without the extension. This paper proposes a method to extend the unambiguous range by changing the repetition range. Firstly, the method of dual-comb ranging and the principle of extending the non-ambiguity range were introduced. Secondly, the two implementations of changing single repetition frequency and switching repetition frequency were compared through simulation. Then, according to the simulated results, the effective conditions and theoretical maximum range of extended ranging were clarified. Finally, a long absolute distance measurement was designed and the ranging results of switching repetition frequency were compared with the conventional incremental interferometer, which proves that this method is reliable for extending the non-ambiguous range.

The error coefficients calibration of inertial measurement units (IMUs) is an essential step for strapdown inertial navigation systems (SINSs), and the system-level calibration is the most prevalent method. To satisfy the need for high-precision attitude measurement in large-scale shipboard radar, single axis laser gyro SINSs can be directly fitted on radar and spins with it, feeding back attitude information in real time to determine the radar’s direction. The radar's pitch and roll axes can only rotate from -45° to +45°, however the radar heading axis may revolve at any angle by rotating the radar base. For single axis laser gyros SINS with rotation angle constraints, this paper proposes an on-line self-calibration solution. The error model of IMU is established in the study, and the 33-dimensional Kalman filter is applied to estimate the error parameters including the bias, scale factor errors, installation errors, inner-arm errors and quadratic errors. In order to solve the online self-calibration problem of IMU with limited rotation angle, we proposed a 17-step rotation scheme based on the errors transmission characteristics to excite and separate the parameters. The feasibility of calibration scheme is demonstrated by simulation, and results show that this online-calibration method can accurately calibrate the remaining 24 error parameters, except for the accelerometer’s z-axis bias, z-axis scale factor, and z-axis quadratic error. We conducted another simulation without considering the accelerometer’s z-axis quadratic error. Results show that all the calibration results of error parameters can meet the accuracy requirements by using the 17-step rotation scheme.

In recent years, besides higher spatial resolution, higher temporal resolution and higher spectral resolution, extending the effective working time of satellite platform based aerospace paid much attention. And Low-Light-Level (LLL) remote sensing technology in visible band is one of the ways to achieve the goal. LLL remote-sensing camera has become a novel subject for the development of aerospace optical remote-sensing payloads. In this manuscript, first the status quo and trend of LLL remote sensing technology is made a comprehensive introduction. After that, centering on the crucial technique to realize the Low-Light-Level sensing, several different implementation ways are made a comparison both from the theoretical viewpoint and experiment demonstration. Finally, some advices are given on how to develop aerospace LLL remote sensing techniques based on the existing research results.

This paper firstly obtains a set of images with different resolutions by down-sampling the original image, so that there is always a point target in the set of images for targets of different scales. Then, according to the characteristic that the point target exhibits a Gaussian-like distribution, a curvature-based filtering algorithm is used for the group of images to suppress the background and extract the feature points. For the feature points extracted stably from multiple frames, they are correlated to form tracks. Aiming at the problem that the motion law of background points is difficult to be counted due to the insufficient number of background points in low resolution images. This paper counts and analyzes the relationship between the track velocity of background points in images with different resolutions. It is found that the average velocity fluctuation of the background points in the images with different resolutions is basically the same, and has a multiple relationship. According to this relationship, this paper adopts the method of velocity mapping to multiply the velocity of the track in the low-resolution image by the multiple relationship, and perform unified clustering with the track in the high-resolution image. This ensures that the background point track has a large number of samples and improves the stability of the clustering under the premise that the background point track has the same motion law. Through the unified clustering of all tracks, the target tracks at each resolution can be finally screened out.

Based on the unique color separation characteristics of HSI space, noise removal of color images contaminated by high noise is investigated. The color image is first projected into the color feature space HSI, and the color information is separated from the luminance feature information, and then the color components H and S in this space are processed by the distance threshold denoising method in polar coordinates to remove the noise without distorting the color. At the same time, the luminance feature component I is guided filtered to effectively remove the noise while preserving the edge information of the original image; finally, the corresponding inverse conversion is performed to obtain the final color image. The algorithm has some improvement in eliminating color noise, maintaining hue, and protecting image details compared with previous algorithms, which is more in line with the visual requirements of human eyes.

Over the past several years, ghost imaging has made remarkable achievements in poor optical conditions, including underwater imaging works. This study describes the interactions between environmental interference and experimental results of ghost imaging applied to underwater scenarios deduced by mathematical processes and related researches findings. In this paper, the causes of notable optical influences: absorption, scattering, and turbulence are firstly presented in the form of statistical mathematics; sequentially, at the level of complex amplitude in wave optics, the experimental principle: second-order correlation are calculated as a basic for subsequent discussion in physical illustration; further, mainly from existing researches, the text expounds the specific influence of environmental and experimental factors on the imaging quality with above-mentioned models.

Small moving targets with low signal-to-noise ratio have the characteristics of weak intensity and small size. For stationary targets, it can be enhanced by the time-domain multi-frame accumulation algorithm. However, for small moving targets, the traditional direct multi-frame accumulation method cannot effectively enhance the target due to the change of the position of the target between frames and the spread of target energy. Based on this feature, this paper proposes an enhancement method based on uniform moving small targets. Because the target moves at a uniform speed between frames, the target smear image can be obtained by directly accumulating multiple frames of the collected target image sequence according to the stationary target, and then according to the smear information, the real moving speed of the target can be reversed. Finally, according to this speed, the small target image sequence is shifted and accumulated by multiple frames. In order to verify the effectiveness of the proposed method, the experiment is designed to simulate the motion of a small target by carrying a faint point light source on a motorized slide at constant speed, collecting data for correlation processing. The experimental results show that the method proposed in this paper can quickly and accurately estimate the speed of the small target moving between frames. The accumulation of small target images shifted according to this speed can significantly enhance the target and improve the signal-to-noise ratio.

The continued miniaturization of smart sensor chips has driven the portability of smart medical care. Although the traditional health parameter monitoring equipment is accurate in measurement, it is greatly limited in time and space due to factors such as bulky size, high cost, complex operation, and inconvenience in use. In view of the above problems, this paper proposes a dual-spectrum mobile phone ring buckle health monitoring system solution with high integration, high precision and small size. The signal is better at the fingertips, with relatively little high frequency noise and baseline drift. The dual-spectrum mobile phone ring buckle health monitoring system studied in this paper can accurately measure pulse waveform, heart rate value, blood oxygen value and other information. It supports Bluetooth communication and can remotely send the collected data to the mobile APP. The monitoring system adopts the reflection photoelectric pulse wave detection method to realize non-invasive acquisition. The photoplethysmography (PPG) signal is collected by using red light and infrared light double LED. Through filtering, differential threshold method and other algorithms, the heart rate value and blood oxygen value are obtained from the original pulse wave. The system is small in size, low in power consumption and high in precision. The experimental results show that the heart rate error of the integrated system can reach ±2%+2 beats/min, and the blood oxygen error can reach ±2% within the range of 70-100.

High-temperature field detection has important application value in the industrial and military fields. The three-dimensional structure reconstruction of flame is of great significance to carry out the finite element division of the temperature field. However, because the flame is a self-luminous fluid, the flame pictures obtained directly by the camera lack characteristic information, and the use of many three-dimensional reconstruction technologies directly performs topographic reconstruction with low accuracy. In this study, MATLAB software was used to conduct simulation experiments to study the accuracy of the 3D structure of flame reconstructed by chemiluminescence computed tomography. A single Gaussian peak was used to simulate a symmetrical flame, and a 2D projection of the flame was obtained according to a simplified chemiluminescence tomography model. The additive algebraic reconstruction method was used in this study. (Additive Algebra Reconstruction Technique) reconstructs the three-dimensional structure of the flame. The resolutions of 256px, 512px, 1024px triple-projection images are set respectively, as well as the different number of channels. The mean error is used for quantification to evaluate the accuracy of the reconstruction results. The experimental results show that the resolution of 512px and the number of channels of 13 converge after eight iterations, and the reconstruction accuracy is better than that of the projection resolution of 256px. At the same time, the reconstruction speed of the ART algorithm at 512px is much faster than that at 1024px. At the same resolution, the reconstruction accuracy increases with more channels.

Compared with the traditional electronic line delay, the optical fiber delay line has the advantages of small size, light weight, wide bandwidth, low loss, and strong anti-interference ability. Fiber optic transmission delay measurement technology has a wide range of applications in early warning, communications, navigation, ranging, remote mapping, etc. Traditional optical methods of measuring time intervals can achieve a high degree of accuracy, but they are complex to use, difficult to set up, susceptible to interference, have a limited measurement range and are expensive. Time interval measurement methods for electrical signals can be broadly classified into two categories: analogue and digital. With the continuous development of semiconductor technology and the increasing maturity of digital circuit technology, digital methods now have an increasingly wide range of practical applications, not only because analogue methods are very sensitive to ambient temperature, but also because they require relatively long conversion times, are susceptible to external disturbances and are difficult to integrate. Correlation detection is a very common method for processing signals in the time domain, and is used in correlation detection, delay measurement and signal identification.

The development of high precision fiber optic gyroscope (HFOG) is of great strategic significance to a country's industrial and national defense science and technology. Optical fiber coil is the key to guarantee the accuracy and long-term stability of HFOG, and the adhesive is an important factor for the stability of optical fiber coil performance. In order to improve the temperature characteristics of HFOG, this study carried out the research on the technology of high thermal conductivity adhesive doped with high thermal conductive filler to improve its thermal conductivity (κ), and prepared a high thermal conductivity coil potting adhesive with excellent heat transfer and heat dissipation performance. By designing the composition ratio and block molecular structure with alternating soft and hard segments, the balance of glass transition temperature (Tg) and Yong’s modulus (Eˊ) was obtained, which can make the temperature field distribution of the optical fiber coil more uniformly, reduce the stress in the coil after curing, reduce the coil temperature errors. The above studies suppress the temperature drift and improve the overall accuracy of HFOG.

Many industrial gases and aerosols have rich spectral characteristics in the long-wave infrared band, which can play an important role in gas detection and chemical protection. In this paper, the principle of Gaussian filtering and the establishment process of Gaussian operator are introduced, and a noise suppression method of long-wave infrared Fourier spectrometer at various piecewise is proposed. The amplitude of interference signal is mapped into noise estimation weight, and then the size and weight of Gaussian filter window are selected to realize adaptive Gaussian filtering of noise estimation weight. Compared with median filtering, mean filtering and single window Gaussian filtering, the experiment shows that the proposed algorithm can protect the spectral energy and suppress the influence of noise on the signal, and the filtering effect is obvious.

Improving the centroid and grayscale extraction accuracy of point targets is of great significance to the long distance detection system. There is a drop in centroid accuracy due to pixel sampling. For point targets, due to the small number of target pixels, the positioning accuracy is generally sub-pixel, and the use of optical dispersion to increase the number of target point pixels will reduce the signal-to-noise ratio of the point target, thereby reducing the detection distance of the system. In addition, there is a gap between the pixels of the infrared detector, and the grayscale response of the detector cannot reflect the real radiation intensity of the target. This paper simulates the point spread function based on the Gaussian function .The four parameters(the center coordinate, the width and the peak value) of the Gaussian function are estimated by a proposed optimization algorithm based on the obtained grayscale information of the point target. The results show that the grayscale extraction error is reduced from 35% of the grayscale summation algorithm to less than 10%, and the centroid error is also improved compared with the traditional centroid calculation algorithm.

Optical lenses, high precision, easy to wear, difficult to process, has always been a difficult point in high-precision detection. In order to meet the needs of the surface shape detection of optical mirrors of different surfaces in the milling, grinding or initial throwing stage, this paper elaborates how to complete the detection of multiple samples of optical mirrors based on CAD models in three coordinate detection to improve efficiency and improve the quality of surface inspection. At the same time, the application scheme of white light confocal technology of Hexagon's LR probe is studied, how to further improve the product detection efficiency and the advantages of ensuring the quality of non-contact measurement, and the dual application can professionally and intuitively guide the design, process and processing of technical improvements, and can also solve the problem of optical lens inspection.

Space debris identification and localization has been studied for a long time at home and abroad, but there are still shortcomings in the detection of very low SNR small targets, especially the detection and recognition of very low SNR faint small targets submerged in the dense galactic background stars. In order to effectively target detection, background removal is essential to distinguish between the target and the stars through the accumulation of judgement block number of stars closely adjacent to judge, if the judgment of the block star is a closely adjacent number more than a set threshold, so that the point for stars, on the other hand, argue that the point as the goal is to be detected, then, to the star point of the block. The results of the algorithm show that, according to different star map images, the size of matrix block and the threshold of star point can be modified to achieve better star removal effect.

The target will be affected by the solar radiation, the earth radiation and the earth's reflected solar radiation during the flight. Due to the closeness of the earth to the target, the spatial position of the target has a great influence on the received radiative heat flux. At present, in many studies on the radiation characteristics of the target, researchers regard the earth as a black body with uniform temperature for equivalent replacement, which will cause certain errors in the calculation results. Therefore, based on the radiation transfer theory and spherical model, this paper analyzes the spatial position relationship between the target and the earth and the sun under different attitudes, calculates the angular coefficient relationship between solar radiation, earth radiation and the earth's reflected solar radiation, and build a simulation model of heat flux received by space target. The simulation results show that for the shadow environment, the target is only affected by the radiation of the earth. The model constructed in this paper can achieve refined modeling of the earth with higher accuracy than traditional methods. For environments with solar radiation, although the introduction of the sun compresses the effect of Earth's radiation, the effect of Earth's albedo needs to be considered in Earth modeling because the target receives a large amount of Earth-reflected solar radiation.

Point-clutter and strip wave often exist in infrared images of sea surface, which will cause great disturbance to ship target detection. In most cases, the noise in infrared image can be suppressed by image denoising. However these sea clutter are different from typical noise in infrared images and cannot be removed by traditional denoising methods. We study the background characteristics of infrared sea clutter and propose a sea clutter suppression method based on gradient filtering. Our method can keep the details of ship target while smoothing the clutter background, and can be used as an effective preprocessing method for infrared ship target detection. The experimental results show that our method is superior to the other four methods in sea clutter suppression and measurement indexes. Our method can effectively suppress the infrared clutter background and keep the structural characteristics and details of the ship target, which greatly enhances the separability of the ship target. In the future, our method needs to further improve the timeliness and reduce the algorithm complexity.

Man-made target detection in the natural background is the core problem of high-resolution optical remote sensing image interpretation, and it is an important application direction in the target recognition, situation awareness, and other fields. This paper proposes a man-made target detection method based on red-edge spectral information in the natural background. In this method, the red-edge spectrum information of vegetation is used to suppress background interference and narrow the search area in large remote sensing images, to improve the probability of target detection. The automatic extraction model of man-made targets is trained by the public dataset COD10K and self-constructed remote sensing dataset, and detection experiments are carried out by using the multispectral images from the WorldView-3 satellite and the Sentinel-2 A/B satellites. The experimental results show that the proposed algorithm has high detection accuracy and fast detection speed for the green runway, green buildings, and another man-made targets in the forest or grassland. Compared with the traditional man-made target detection algorithm, this method is more suitable for the rapid search of large area remote sensing images.

This paper reports a new optical suppression method of fiber optic gyroscope and its relative intensity noise. Using the optimal design of all fiber devices, the relative intensity noise of light source is suppressed at low cost without changing the circuit and algorithm, and the signal-to-noise ratio of gyroscope is improved. The accuracy of fiber optic gyroscope can be improved by 12%, which is very suitable for the performance improvement of fiber optic gyroscope.

To reduce the measurement error in the vibration scenario, this paper proposes a cooperative post-processing method based on the measured overload information and Kalman filter. In order to make the equation of motion more accurately, the target measures and shares its overload information to the source. The source then calculates the overall overload information and perform Kalman filter to the real-time measured data. The performance evaluation is carried out through a physical measurement test and a post-processing simulation. The real-time measuring data is updated at 200Hz while the vibration frequency is about 1Hz. The simulation results show that the proposed method can reduce the measurement error by about 9.9 times and is insensitive to the common time synchronization error and overload measurement error.

Stray light contamination is an important factor affecting the nighttime remote sensing image quality, especially affecting the quantitative application of low-light-level remote sensing data. VIIRS Day/Night Band(DNB) data is the most widely used nighttime low-light-level data in the world. However, the stray light contamination impacts the DNB sensor’s nighttime scenes. In this paper, we analyzed the characteristics of VIIRS DNB stray light and designed a simple and effective stray light correction method based on automatic region division. We preprocessed the data that meet certain solar zenith angle (SZA) requirements to obtain the true stray light data. An automatic region division method according to the SZA is designed to find the specific area affected by stray light and get the boundary of different region. Polynomial curve fitting based on least square method was used to get the mathematical model of the stray light. Then the mathematical model was used to do the stray light correction. We use the DNB northern hemisphere Earth view data to verify this method. Experimental result shows that the proposed method can effectively remove stray light and restore the surface information while preserving the radiation information.

Artificial intelligence (AI) has been widely used in various fields of physics and engineering. In this work, we introduce the model-based reinforcement learning (MBRL), which is an important branch of machine learning, to the laser frequency sweep control for frequency modualted continous wave (FMCW) light detection and range (LiDAR). With the well designed neural network structure, the experimental results with control represent a significant improvement in the linearity of laser frequency sweep indicating that our proposed MBRL control method has the potential for complicated optical systems control.

High-Precision Fiber Optic Gyroscope (HPFOG) is the core sensor of the long-endurance fiber optic inertial navigation system. The improvement of the positioning accuracy of the inertial navigation system depends on the improvement of the bias performance and the scale performance of the gyroscope. The broadband ASE light source can effectively suppress the noise such as Kerr effect and Rayleigh scattering in the optical path of the FOG. The flatness of the output spectrum of the ASE light source also affects the scale of the FOG. In this paper, the influence of broadband fiber light source on the bias performance and scaling performance of HPFOG is analyzed theoretically, and the design of a high-flatness C+L band broadband ASE light source is developed. By analyzing the conditions of the output spectrum of the ASE light source from the C-band to the L-band until the C+L band is formed, the pump light power and the length of the erbium-doped fiber are optimized, and the output spectral width, power and spectral flatness of the ASE light source are simultaneously improved. Performance, the developed C+L band broad-spectrum ASE light source has a spectral width of 80nm and a flatness of less than 1.5dB. Subsequently, this paper compares the performance of HPFOG using traditional Gaussian ASE light sources and high-flatness C+L band light sources. The experimental results show that although the spectral symmetry of the C+L band broad ASE light source is weaker than that of the Gaussian spectrum ASE light source, but the scale factor performance of HPFOG is similar, and there is no obvious impact. The key is that the use of high-flat C+L band broad ASE light source significantly improves the bias stability of HPFOG. The normalized index shows that the 100s bias stability is improved by 30%.

The laser scattering properties of the target, which is characterized by the laser radar cross section (LRCS), are the theoretical basis of the target detection and recognition of a lidar system, and play an important role in the design and evaluation of a lidar system. We calculated the LRCS of the vehicle based on the in-field measurement and numerical simulation. The experimental results demonstrate that the trend of simulated data of the vehicle and the corresponding experimental data is qualitatively similar, but there is a big difference in absolute value. Based on this, we can optimize the approaches for researching the laser scattering properties of the target.

For traditional HDR fusion algorithm based on mapping functions, the artificial determination of the over exposure region often ignores the spatial distribution and the relation of pixels of the image brightness. In this paper, a stimulated HDR fusion algorithm based on pulse coupled neural network is proposed. For the proposed algorithm, first obtain the external stimuli according to the maximum image brightness, calculate whether the pixel “fires” or not and determine the over exposure region. Then alter the value of external stimuli to perform iteration and construct judgment matrix to make sure that every pixel in the image “fires”. The image irradiance is linear with the illuminance and exposure time. Obtain the brightness mapping function using linear fitting, and synthetize HDR image with over exposure correction algorithm to eliminate artifacts. The algorithm mainly has the following advantages: 1. It fully considers the spatial distribution of the image brightness. 2. For the imaging of different scenes, it self-adapts to separate exposure regions. 3. It performs mapping according to the imaging principles, and obtains the mapping function without the exposure time. 4. It reduces the quantitative error of synthetizing image, and the artifacts in the transition region. The algorithm proposed in this paper is experimented under multiple scenes, and the image entropy and spatial frequency are improved greatly.

Optical rotatory dispersion (ORD) is an important property of chiral material. How to obtain the ORD curve of chiral material quickly and accurately has attracted great attention from researchers. This work presents a measurement method of ORD based on a polarization axis finder (PAF) and a conical lens (CL). The PAF can modulate the collimated broad-spectrum beam spatially to form an “hourglass” intensity pattern, and the CL can disperse the polarization information of light of different wavelengths to different positions in space. The use of the PAF and the CL enables the ORD of the sample to be obtained with only a single image. We perform a theoretical analysis of this method to prove it is feasible and verify it experimentally with left-hand quartz (LHQ) as the sample. Both theoretical and experimental results prove that this method is a fast and effective way to determine the ORD of chiral substances.

Drought stress is the main factor affecting plant grown and development. Chlorophyll fluorescence was chosen as research object to study the effects of drought stress on the growth of Longjing tea seedlings crops. A chlorophyll fluorescence collection system was designed with LED, CCD and filter. Longjing tea seedling with good growth were selected for drought treatment. The tea seedlings should be dark treatment before each experiment. Using LED lamps actively induced the emission fluorescence of tea seedlings, and the images were collected in the same time period for 8 consecutive days. The chlorophyll fluorescence quenching curve was drawn through the mean gray value of the images after preprocessing with median filter. We proposed a new method for evaluating fluorescence quenching curves using slope index, named the slope fluorescence index (SFI). The range of the gray scale mean at the same time in 1-8 days is calculated, the relative errors of range were calculated over the selected time range and determining the time range of range stability. Within the time range, correlation model between each point on the curves and the stress days was established to find a point with the largest correlation coefficient R 2 . The results showed that there was the highest correlation between the SFI of fluorescence quenching curve at 327s and the days of drought stress (determinant coefficient R 2=0.94021). Slope fluorescence index (SFI) is used to evaluate chlorophyll fluorescence quenching curve, which will provide a new idea for monitoring plant growth under stress.

There are three common scanning schemes for large area imaging for airborne camera—multi lens splicing, circumferential scanning or reciprocating scanning. However, the lens splicing form requires multiple lenses, and the system is cumbersome. The circumferential scanning imaging obtains a wide area image through azimuth continuous scanning and the field of view in the pitching direction of this imaging method is a fixed value. And the imaging efficiency of reciprocating scanning form is low due to the need for multiple mechanism turns. In this paper, a new spiral scanning scheme method over large area imaging is proposed, which carries the area array camera on the two-dimensional platform with external azimuth gimbal and internal pitch gimbal. Scanning in azimuth combined with pitch motion, the spiral scanning trail is composed for wide-area imaging, and this method requires only one area array camera and only one rotation in pitch direction in one imaging process, which has high imagery efficiency. At the same time, the spiral dynamic scanning algorithm which can isolate attitude disturbance and compensate flight movement to achieve the scanning imaging for large area of the specified area is deduced. Then the implementation form of the scanning method is also derived. Finally, we take some simulation to test the method. The results show that the spiral scanning algorithm can compensate the attitude disturbance and aircraft attitude disturbance, and can obtain the staring imaging of 254km2 (mapping radius of 9km) in 3.8 seconds, when the field of view angle of area array camera is 7.5 °× 11.25 °, the flight speed is 360km/h, the azimuth attitude disturbance is 15 °, the pitch attitude disturbance is 15 °, and the roll attitude disturbance is 8 °, at the flight altitude of 7500m. Therefore, the spiral scanning algorithm scheme is suitable for wide area imaging of moving carrier and has certain significance for the research of wide area scanning imaging system.

The important characteristic of binocular vision system is that it can form stereo parallax. Subject to the limitation of "no-similar" imaging principle, the parallax of object points in binocular vision with large FOV is not necessarily distinguishable by the detector, but the distinguishable parallax is the basis of realizing stereo vision. Based on the ideal theoretical model, this section will establish a general structure of large FOV binocular stereo vision parallax model, learn from the relevant concepts of human binocular vision, conduct theoretical research on the characteristics of large FOV binocular stereo vision and the influence of system parameters, analyze the characteristics of image parallax, and compare it with the image parallax formed by small FOV binocular vision. This paper also simulates the generation of parallax in large FOV binocular vision image to verify the correctness of the theoretical analysis. The research of this paper plays a role in expanding the application of binocular vision with large FOV, and can also provide reference for the design of system parameters.

For the current ground-based space target surveillance system in China, the task response time is long, the target monitoring system is time-sensitive, and the space-based on-orbit monitoring current monitoring system usually has a small field of view, and the field of view is generally 6°, the monitoring range is limited, and the tracking arc is limited. This paper proposes a design of space-based large field of view monitoring camera. The selection and experimental analysis of high quantum efficiency and low noise detectors, detector refrigeration design and thermal test verification, big angle and high suppression ratio stray light design, this key points of high sensitivity detection camera for dim target are discussed in this paper, and lay the foundation for quickly acquiring the position and orbit information capability of long-range dim targets, providing high-precision cataloging of fast-moving dark space targets, improving the monitoring performance and real-time performance of surveillance systems in China.

The infrared multi-spectral camera on near-space vehicle had the characteristics of high spatial resolution, high time resolution. A new dual-channel infrared multi-spectral remote sensing camera was developed. It included a middle wave (MW) channel (3.7μm~4.8μm) and a long wave (LW) channel (8μμm~12.5μm). The optical system adopted a refract system, a dichroic beam-splitter was utilized to separate LM form MW. The MW and LW channel all had five spectral bands , and filter wheel assemblies were used to split the in-coming MW and LW radiant flux into 5 spectral bands. The optical system aperture was 45mm, and the focal of the two infrared channels were 62.5m. The full field modulation transfer function (MTF) of MW channel was over 0.67, and the MTF of LW was over 0.329. The focal of MW and LW channel had 640×512 pixels, and the pixel size was 25μm. Because of the high integrated design, the total weight of the camera was 18.5kg. The camera would be used to monitor the fire and the forest fires and marine pollution on a airship.

The reasonable design of the dynamic range of spaceborne remote sensor is the basic guarantee for its effective observation in-orbit, but the complex radiation characteristics of the earth-atmosphere system and other factors have brought some1 challenges to its design. Aiming at the Polarized Scanning Atmospheric Corrector (PSAC) on board Huanjing-2A/B(HJ-2A/B) satellite, the dynamic range of apparent radiance observed by PSAC is analyzed and obtained according to its detection target and band setting, based on the method of statistics of historical data of remote sensors such as Moderate-resolution Imaging Spectroradiometer (MODIS), considering the complex radiation characteristics of earth atmosphere system and scale effect. In order to meet the requirements of dynamic range design and ensure better radiation resolution, PSAC designed four gear adjustable electronic gain (relative gain is 1,2,3,4), and carried out the system radiation response gain adjustment and dynamic range test under laboratory conditions. The statistical results of on orbit observation data of PSAC show that the design results of its dynamic range meet the needs of on-orbit observation application, and lay a foundation for the retrieval of atmospheric and aerosol parameters and the realization of atmospheric correction objectives.

The lenticular grating is the most widely adopted core light control device in the naked-eye autostereoscopic display technology, which has a certain inclination angle with the subpixels on the liquid crystal display to eliminate the moirefringes. However, the segmentation of the sub-pixels by the edge of the lenticular lens unit will inevitably lead to the sawtooth of the displayed three-dimensional image. Therefore, a weighted optimization algorithm for synthetic images is proposed in this paper, which is based on the sub-pixel segmentation area and adjacent pixel values for correction. In the experiment, the sawtooth of the reconstructed image is suppressed and the display quality is improved.

Retinal projection display (RPD) is considered as a better solution for near-eye displays (NEDs). It can be used for the augmented-reality (AR) and virtual-reality (VR) applications. In this paper, we propose the RPD system with extended eyebox solution based on freeform holographic elements, realizing the 3×3 viewpoints array in two-dimensional directions on the pupil plane. The viewpoints spacing is 3mm, the FOV of each viewpoint is close to 40°×40°, and the eye relief is 25 mm, which can effectively overcome the eyebox limitation of the conventional RPD system. Detailed procedures of the design and analysis process of RPD system with extended eyebox will be demonstrated in this paper.

Due to the limitation of the measurement accuracy of classical radio signals, the time comparison accuracy can only reach ns level. In this paper, a time comparison scheme of BeiDou system based on microwave-optical entangled signal is proposed, which effectively combines the long-distance transmission advantage of microwave signal with the single photon detection advantage of optical signal by electro-opto-mechanical converter, and the phase difference is solved by a phase conjugate processor ,so as to calculate the accurate time difference information. Through theoretical analysis and simulation, it is proved that even if the quantum signal is under the condition of low entanglement degree, the proposed scheme can improve the time comparison accuracy to the ps level.

A theoretical model is proposed to construct high-fidelity arbitrary single qubit gates with geometric phase via a pair of non-adiabatic two-color pulses (TCP) with multiple degrees of freedom interacting with a resonant Λ system. The amplitudes and phases of the TCP are divided into three segments under specific conditions. Compared with the traditional gate operations via single-loop multiple pulses, our model provides a shorter evolution path for small rotation gates, reduces the population in the excited state by 40%, and increases the robustness against the Rabi error. The model is applicable to a single-ion rare-earth-ions (REI) system, where Eu³⁺ ions doped in an Y₂SiO₅ crystal is considered. Simulations show that the operational fidelities of NOT gate and Hadamard gate are both above 99.8% with an evolution time of 3 μs.

We proposed a theoretical protocol to generate robust pulses for executing an arbitrary nonadiabatic holonomic quantum gate operations via reverse engineering. Compared with the traditional scheme that the pulse area needs to satisfy the condition 0 Ω dt = π, the reverse engineering scheme no longer requires this constraint, which greatly improves the flexibility of pulse designing. By optimizing the envelope of the pulses, we show that the gate operations are more robust against the frequency detuning than the traditional scheme. In the meanwhile, we also improve the robustness of the pulse against Rabi frequency fluctuations by utilizing the perturbation theory. The robust pulses can be applied to other ensemble qubit systems to realize quantum error correction, qubit initialization, and quantum gate operations, such as ensemble nitrogen-vacancy center systems, superconducting qubit systems, and other systems where qubits are addressed in frequency.

"Tianzhou-1" cargo spacecraft is an important part of China's manned stations. Its main task is to add propellant and transport goods for the manned stations, and bring the station waste back to the atmosphere for burning. The "Tianzhou1" series cargo spacecraft is the backbone of the material supply of China's manned stations. The energy of cargo spacecraft in space comes from the flexible solar wing, but the solar wing is easy to vibrate by the unstable excitation from the platform. To solve this problem, the vibration response of the flexible solar wing system is analyzed, and the dynamic model of the flexible solar wing is established. On this basis, the control system is designed by using negative velocity feedback and linear quadratic optimal regulator, and then the vibration is suppressed. Finally, the experimental verification of vibration control of flexible solar wing of cargo spacecraft is realized by designing the experimental system of peripheral circuit, driving circuit and position detection circuit of processor based on DSP + FPGA. Through experimental verification, the system can realize the vibration suppression function of the extension mechanism with high disturbance, and realize the engineering application that the large flexible solar wing can expand and close repeatedly and smoothly. It has certain application value and provides reference for subsequent engineering applications.

As a high-precision position actuator, the voice coil motor (VCM) is widely used in technology of segmented mirror and mirror shape correction in space telescope. In response to the adverse effects of internal and external disturbances on the precision positioning of the VCM, an improved particle swarm optimization (PSO) based active disturbance rejection control (ADRC) VCM position control model is proposed in this paper. Our model is able to present a reasonable solution to the problem that ADRC has numerous parameters which are knotty to configure. In order to prevent precocious convergence or falling into local optimal, a variable weight factor search method is proposed. MATLAB and Simulink are employed for co-simulation and control experiment are designed. The simulation results show that compared with traditional PID control, the control model designed in this paper has better dynamic performance, higher tracking accuracy and better disturbance rejection performance, and it is suitable for high-precision position control under complex environment with a bright engineering application prospect.

This article aiming at the high performance requirements of the space camera mirror assembly, and in order to ensure that the space camera main mirror has good surface shape accuracy and high first-order natural frequency, the mirror and flexible support structure are studied and designed. First, according to the selection principle of the mirror material, SiC is selected as the mirror blank material of the mirror. According to the empirical formula, the three-point support scheme on the back of the mirror and the structural size parameters of the mirror body are determined. And a flexible support structure with multi-axis flexible hinge and dual-axis flexible hinge in series is designed for the mirror. Finally, the parameter optimization method is used to optimize the position radius of the mirror back support hole and the key dimensions of the flexible structure. The static analysis and modal analysis of the mirror assembly were carried out using the finite element method. The results show that the surface shape accuracy of the mirror is 0.015λ nm, the first-order natural frequency of the mirror is 145.57Hz, the weight is 135.35Kg, and the lightweight rate is 87.57%.

Spaceborne two-dimensional turntable is the main carrier of the space camera and other optoelectronic equipment, and the stability of the thin-walled angular contact ball bearings used in its shaft system will affect the control accuracy and service life of the satellite. Research on slip rate, the deviation ratio of centroid whirl velocity and vibration of bearing with different pocket clearances, outer clearances and velocity and axial loads. For 71928AC type angular contact ball bearing, when pocket clearance is between 0.30-0.40mm, outer clearance is 1.60mm, the cage of bearing has better stability. According to the experimental results, after the parameter optimization, the bearing stability is enhanced. The research results provide a theoretical basis for the optimal design of angular contact ball bearing cages.