A novel optimization method for star-sensor data processing

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• 作者：Jian Han ; ^{252942408@163.com} ; Changhong Wang ^{cwang@hit.edu.cn} ; Baohua Li ^{libaohua@hit.edu.cn}
• 关键词：Star-sensor ; De-noise ; Allan variance ; Wavelet analysis ; High accuracy
• 刊名：Optik - International Journal for Light and Electron Optics
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：132
• 期：Complete
• 页码：192-202
• 全文大小：2485 K
• 卷排序：132

文摘

A novel optimization method for star sensor data processing has been proposed in this paper, by which the stability and accuracy of star sensor attitude outputs have been improved. Aiming at the problem that the star sensor has unacceptable single measurement error, which reduces the accuracy of navigation and dissatisfies the requirement of high accuracy in navigation system. Utilizing improved transformation, extraction, interpolation and filtering, then using wavelet analysis integrated with Allan variance, the star-sensor measurement data is processed to solve the problems mentioned above. By adopting this method, the star-sensor can achieve: (1) eliminate outliers accurately, to enhance the ability of error redundancy; (2) smooth and eliminate low frequency trends, to enhance the ability of interference resistance; (3) uniform data with equal interval and make it continuous, to enhance the stability; (4) restrain the internal noise and observation noise, to enhance the signal-noise-ratio; (5) de-noised with improved method, to promote star-sensor attitude output accuracy.