Denoising star map data via sparse representation and dictionary learning

作者：Zhou Mingyuan^*; Shi Ying; Yang Jigang

来源：Optik, 2015, 126(11-12): 1133-1137.

DOI：10.1016/j.ijleo.2015.02.091

• Sparse representation
• Redundant dictionary
• Star pattern recognition
• Noise suppression

As the highest precision devices of celestial navigation system 111, star sensors have been getting more and more attention in recent years. In which the star image positioning and recognition is the key technology of CNS, while the extraction of stars from star maps is the first step. By the background noise, there are some error extractions when traditional methods are used, which can even lead to the failure of star map matching. To solve this problem, a denoising method based on overcomplete sparse representation is presented in this paper. This method uses the adaptive sparse decomposition of star map in the redundant dictionary to process the threshold, as a result, the reliability of star extraction is improved. The experimental results show that the correct rate of this method that extracting star after reducing background noise of star map is close to 100%.

• 出版日期2015
• 单位北京航空航天大学; 北京自动化控制设备研究所