The light curve of space debris can provide the basic target identification information. Photometric data of space target
obtained by ground-based equipment are affected by weather condition, observation equipment, detector performance,
etc. Among these factors, the poor weather condition during the observations could cause worst effects in the
photometric data. The light curves will be smooth and regular under photometric conditions, while irregular in nonphotometric
nights. In addition, we can not distinguish what caused the abnormal brightness variations between weather
and other factors from the traditional photometric data. Our study shows that by obtaining simultaneous light curves of
background stars with an independent telescope close to the main telescope with dedicated observing tactics, we can
verify the influence factors of the photometric variations in non-photometric nights.
Restoration of atmospheric turbulence degraded image is needed to be solved as soon as possible in the field of
astronomical space technology. Owing to the fact that the point spread function of turbulence is unknown, changeable
with time, hard to be described by mathematics models, withal, kinds of noises would be brought during the imaging
processes (such as sensor noise), the image for space target is edge blurred and heavy noised, which making a single
restoration algorithm to reach the requirement of restoration difficult. Focusing the fact that the image for space target
which was fetched during observation by ground-based optical telescopes is heavy noisy turbulence degraded, this paper
discusses the adjustment and reformation of various algorithm structures as well as the selection of various parameters,
after the combination of the nonlinear filter algorithm based on noise spatial characteristics, restoration algorithm of
heavy turbulence degrade image for space target based on regularization, and the statistics theory based EM restoration
algorithm. In order to test the validity of the algorithm, a series of restoration experiments are performed on the heavy
noisy turbulence-degraded images for space target. The experiment results show that the new compound algorithm can
achieve noise restriction and detail preservation simultaneously, which is effective and practical. Withal, the definition
measures and relative definition measures show that the new compound algorithm is better than the traditional
algorithms.
The real-time detection and surveillance of space targets are primary functions of space surveillance system. On account of abundant infrared radiation of the electronic and electromechanical equipments inside satellites, spacecraft, etc., the infrared characteristics of space targets will be very obvious in the cold astrospace background. Therefore, using spaceborne IR detection system is very beneficial to space object detection, especially in the absence of any significant
atmosphere. The key characteristic of spaceborne IR system is passive measurement principle, but not requiring direct sun illumination. This is very proper for the purposes of space control requirements. This paper has theoretically determined the feasibility of the spaceborne IR detection system in using infrared radiation characteristics of a space object and IR imaging sensor to locate and recognize object. According to the requirements of an IR imaging system to modulation contrast, signal-to-noise ratio (SNR) and image size of space object, the paper has discussed infrared radiation characteristics of space object and background, the structure of the system and primary factors which can affect operation range of the system. Results indicate that such parameters as principal design wavelength, spectral band and pixel size of receiving sensor, focal length and aperture diameter of receiving optics system and so on can determine scale, capacity and practicability of detection system. With a 150mm aperture, 800mm focal distance and 13μm IR CCD
imaging pixel dimension, the system could detect a space object with size of 10 m and distance of 200 km. The imaging point of this object would occupy 3×3 pixels point.
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