Mr. Xiliang Tong Profile

Xiliang Tong

at Beijing Institute of Space Mechanics & Electricity

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Proceedings Article | 12 March 2021 Paper

Design and calculation to reduce the polarization sensitivity of COCTS on GEO satellite

Tingting Sun, Zhicheng Shi, Xiliang Tong, Gang Wang, Shoucai Zhang, Pengmei Xu

Proceedings Volume 11763, 1176385 (2021) https://doi.org/10.1117/12.2587557

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The geostationary orbit water color remote sensing satellite has the unique advantage of high time resolution observation, which can accurately obtain the information of ocean color elements, coastal zone observation elements, sea surface temperature and large sea targets. The onboard optical imaging system has the characteristics of large aperture, large incident angle, wide spectrum and multi-channel detection at the same time, so it has high polarization sensitivity. In order to achieve high quantitative application of water-color remote sensing, it is necessary to reduce the influence of polarization sensitivity. According to the characteristics of the water-color remote sensing payload in geostationary orbit, the polarization sensitivity of the system is suppressed by optimizing the structure of the optical system and controlling the polarization sensitivity of the optical film. Then the polarization sensitivity of the system is simulated and modeled by CODEV software, and the macro file based on Mueller matrix is compiled to accurately calculate the polarization of the system in different spectral bands and different fields of view. The results indicated that the polarization sensitivity of the imaging system is better than 1.5% in the visible and near-infrared band.

Proceedings Article | 12 March 2021 Paper

Point target detection methods based on multi-frame association

Xiliang Tong, Gongmin Yu, Feng Zhou, Ke Yin

Proceedings Volume 11763, 1176314 (2021) https://doi.org/10.1117/12.2586204

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Noise and clutter could seriously degrade performance of point target detection, and multi-frame association methods can be used to improve the probability of detection. To figure out detection model and applicability of different methods with multi-frame data, research on SNR (signal to noise ratio) of multi-frame superposition, multi-frame difference and joint probability methods are carried out. Signal gain and clutter restrain coefficient are proposed to revise general model based on affection of image registration. By analyzing signal variation in multi-frame process, influence of coefficient range and frame number to SNR is obtained. The study concluded that detection performance can be improved by multi-frame association significantly. Different methods are proper for specific scenes. Superposition method is applicable to general clutter scene, difference method for severe clutter scene, and joint probability for rapid changes. Superposition and difference methods are sensitive to image registration and better performance can be achieved at sub-pixel precision. The conclusion of this paper can support index design and detection method selection.

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