Mr. Gongmin Yu Profile

Gongmin Yu

at Beijing Institute of Space Mechanics & Electricity

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Proceedings Article | 12 March 2021 Paper

Analysis of factors affecting of coupling efficiency of the SPIDER

Gongmin Yu, Lei Zhang, Ke Yin, Tianyuan Yang

Proceedings Volume 11763, 117635Q (2021) https://doi.org/10.1117/12.2587270

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The Segmented Planar Imaging Detector for Electro-optical Reconnaissance system obtains target information through microlens and photon integrated circuit, which has the characteristics of small size, light weight and low power consumption, and is one of the research directions of high-resolution remote sensing in the future. This paper analyzes the influence of different waveguide offsets on the coupling efficiency of the system. The maximum coupling efficiency is 0.8145 without waveguide offset, and decreases rapidly with the increase of the offset. Finally, the calculation method of the optimal F number of microlens array is given.

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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