Compact polarimetric (CP) data exploitation is currently of growing interest considering the new generation of such Synthetic Aperture Radar (SAR) systems. These systems offer target detection and classification capabilities comparable to those of polarimetric SARs (PolSAR) with less stringent requirements. A good example is the RADARSAT Constellation Mission (RCM). In this paper, some characteristic CP products are described and effects of CP mode deviation from ideal circular polarization transmit on classifications are modeled. The latter is important for operation of typical CP modes (e.g., RCM). The developed model can be used to estimate the ellipticity variation from CP measured data, and hence, calibrate the classification products.
Polarization orientation angle (POA) correction to compensate for terrain effects on polarimetric SAR data has been investigated in the literature. POA rotation can be derived from digital elevation model (DEM) and/or from polarimetric SAR (PolSAR) data through covariance/coherency analysis. A robust analytic model connecting PolSAR data and products (e.g., POA) to target/scene terrain characteristics can serve two main objectives. First is to correct and calibrate PolSAR data acquired from different SARs when DEM is available. Second is to model terrain through inverse solution of POAs derived from PolSAR data analysis. This formalism has been developed and is presented here. Effectiveness of the technique in providing both forward (POAs from DEM) and inverse (DEM from POAs) solutions is explored through imagery product examples and simulations.
KEYWORDS: Terahertz radiation, Resonators, Biosensors, Sensors, Waveguides, Continuous wave operation, Molecules, Signal generators, Antennas, Signal to noise ratio
An integrated continuous-wave (CW) terahertz biosensor is proposed based on an edge-coupled terahertz photomixer source with guided-wave optical excitation scheme. In this device, two laser beams are guided inside an optical dielectric waveguide structure and being gradually absorbed by an overlying ultra-fast photoabsorbing layer, wherein a terahertz signal is generated due to photomixing phenomenon. The generated THz signal is guided by a coplanar-stripline (CPS) and is coupled to an integrated CPS resonator, which acts as a sample carrier and transducer. After interaction by bio-sample, terahertz wave is guided by a CPS line to a wide-band antenna and is detected by a THz power detector. Our performance analysis for the proposed CW terahertz biosensor supports the feasibility of the whole idea very well. The proposed device is attractive for system-on-a-chip terahertz sensors and spectrometers.
Training classifiers individually, and then fusing their results, has the potential to improve classification accuracy; often,
dramatic improvements are realized. In this paper we examine how training classifiers using multiple polarimetric
features such as the Cloude-Pottier decomposition, even and odd bounce and the Polarimetric Whitening filter and then
fusing their results affects performance of ship classification. We explore and compare two currently competing
technologies of classifier bagging and classifier boosting for classifier fusion and introduce a new approach which
conducts a search through solution space to configure an optimal classifier given a library of classifiers and features. A
related and important facet of this work is feature selection and feature reduction methods. We explore how the selection
of different features affects classification performance. We also explore estimates of the classifier error and provide
estimates for noise bounds on the data and compare performance of the different methods compared to the noise present
in data.
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