Mr. Modan Liu Profile

Modan Liu

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Proceedings Article | 30 April 2024 Paper

Electronic design of a spatial low-light camera

Yuan Yuan, Ming Liu, Modan Liu, Xin Li, Yan Chen, Qi Tang

Proceedings Volume 13157, 131570G (2024) https://doi.org/10.1117/12.3015904

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In modern life, it is necessary to image certain targets under low-light conditions such as dark night or morning dusk, and low-light night vision technology is one of the main technologies to expand the night visual perception of the human eye, and low-light remote sensing camera can greatly expand the effective working time range of various spacecraft, so that it can observe, report and warn ground emergencies in a wider period of time. The FPGA-driven scientific-grade CMOS image sensor realizes the imaging function of the low-light camera, and realizes the real-time digital TDI function and automatic exposure algorithm on the FPGA. The results of the exterior imaging experiment show that the contours of buildings, street lamps, trees and wires near the light source can be distinguished under the condition of low-light illumination, and the imaging effect of the low-light camera reaches the index.

Proceedings Article | 4 April 2023 Paper

A space false alarm target detection method based on star information

Haian Zhou, Nuo Nan, Modan Liu, Qi Tang, Guowei Dong

Proceedings Volume 12617, 126170N (2023) https://doi.org/10.1117/12.2663238

KEYWORDS: Stars, Target detection, Target recognition, Cameras, Matrices, Simulations, Satellites, Imaging systems, Satellite imaging, Precision optics

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This paper proposes a space false alarm target detection method based on star information. The central idea is that if a non-star target coincides with the same projected star for several consecutive frames, it is considered as a false alarm target. The implementation steps are: First, project the stars in the star catalog to the image plane. The ID numbers of stars in the star catalog is placed in the data structure of projected star points. Second, based on the matching results of the projected star points and the image points, the image points matching with the stars is obtained, and the non-star target is identified. Third, compare the non-star target with the matching points in each frame. If the Euclidean distance is less than a certain threshold, then the non-star target will be added to the predetermined false alarm target queue. The ID number is placed in the predetermined false alarm target data structure. Fourth, if the ID number of the predetermined false alarm target is the same in several consecutive frames, the target will be regarded as a confirmed false alarm target, and it will be removed from the non-star target queue. Simulations show that the method can effectively realize the identification and elimination of false alarm targets and reduce the false alarm rate.

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