A Compensation Method for Full-Field-of-View Energy Nonuniformity in Dark-and-Weak-Target Simulators

Author:

Quan Fenghuan1,Liu Shi1,Sun Gaofei1,Zhang Jian1,Zhang Yu1,Zhao Bin1,Zhang Jierui1

Affiliation:

1. Aerospace Ground Simulation Test and Testing Technology Institute, Changchun University of Science and Technology, Changchun 130012, China

Abstract

Dark-and-weak-target simulators are used as ground-based calibration devices to test and calibrate the performance metrics of star sensors. However, these simulators are affected by full-field-of-view energy nonuniformity. This problem impacts the quality of output images and the calibration accuracy of sensors and inhibits further improvements in navigational accuracy. In the study reported in this paper, we sought to analyze the factors which affect full-field-of-view energy uniformity in dark-and-weak-target simulators. These include uneven irradiation in backlight sources, the leakage of light from LCD display panels, and the vignetting of collimating optical systems. We then established an energy transfer model of a dark-and-weak-target simulator based on the propagation of a point light source and proposed a self-adaptive compensation algorithm based on pixel-by-pixel fitting. This algorithm used a sensor to capture the output image of a dark-and-weak-target simulator and iteratively calculated the response error matrix of the simulator. Finally, we validated the feasibility and effectiveness of the compensation algorithm by acquiring images using a self-built test system. The results showed that, after compensating an output image of the dark-and-weak-target simulator, the grayscale standard display function (SDF) of the acquired sensor image was reduced by about 50% overall, so the acquisition image was more accurately compensated, and the desired level of grayscale distribution was obtained. This study provides a reference for improving the quality of output images from dark-and-weak-target simulators, so that the working environments of star sensors may be more realistically simulated, and their detection performance improved.

Funder

National Natural Science Foundation of China

innovative and entrepreneurial talents in Jilin Province of China

Jilin province science and technology development plan project of China

Publisher

MDPI AG

Reference19 articles.

1. Shen, C., Ma, C., Gao, W., and Wang, Y. (2024). Hybrid Grid Pattern Star Identification Algorithm Based on Multi-Calibration Star Verification. Sensors, 24.

2. Wu, L., Xu, Q., Wang, H., Lyu, H., and Li, K. (2019). Guide Star Selection for the Three-FOV Daytime Star Sensor. Sensors, 19.

3. Study on the uniformity of high concentration photovoltaic system with array algorithm;Gong;Sol. Energy,2017

4. Improvement of irradiation uniformity by dynamic interference structures of laser array in inertial-confinement-fusion facilities;Zhong;Opt. Commun. J. Devoted Rapid Publ. Short Contrib. Field Opt. Interact. Light Matter,2020

5. Bispectral panoramic corona detection optical system;Wang;J. Photonics,2010

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