One method on refraction star-map simulation

Zhenfei Song; Chen Zhao; Lixin Ren

doi:10.1117/12.2540973

18 December 2019 One method on refraction star-map simulation

Zhenfei Song, Chen Zhao, Lixin Ren

Proceedings Volume 11338, AOPC 2019: Optical Sensing and Imaging Technology; 113380A (2019) https://doi.org/10.1117/12.2540973
Event: Applied Optics and Photonics China (AOPC2019), 2019, Beijing, China

Abstract

High precision star sensor can indirectly gain the information of attitude and orbit by refracted starlight, so that spacecraft can navigate and position autonomously. Due to the high cost of spacecraft launch and development, the functional validation of this technology relies mainly on the ground simulation tests and experiments. At present, less attention is paid to the study on refraction star-map simulation method, and the simulation effects of the existing implementation methods are difficult to meet the engineering requirements. Firstly，by combing the autonomous navigation principle and mathematical model of starlight atmospheric refraction, based on the situation that effective starlight refraction occurs in stratosphere space, a mapping band of refracted starlight is put forward. Then, through three steps including the critical condition of starlight refraction happens in the stratosphere space, the determination method of refracted starlight vector and the angle range of star sensor boresight pointing when the refraction stratosphere space enters the field of view (FOV), a method on refraction star-map simulation proposed in this paper is described in detail. Finally, with the help of MATALB, the refraction star-map simulation is achieved and a sharp contrast of the mapping coordinates of starlight vectors with/without refraction is given, and the effect of simulated star-map is excellent. This method has important engineering application value.

Citation Download Citation

Zhenfei Song, Chen Zhao, and Lixin Ren "One method on refraction star-map simulation", Proc. SPIE 11338, AOPC 2019: Optical Sensing and Imaging Technology, 113380A (18 December 2019); https://doi.org/10.1117/12.2540973

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