Improved multiscale filtering algorithm of multisensor integrated navigation system#br#

doi:10.16708/j.cnki.1000-758X.2020.0046

Abstract

Abstract: Multi-scale filtering algorithm has been successfully used in multisensor integrated navigation system, but this algorithm uses measurement vectors at different times, thus causing heavy computation burden and affecting the system′s real-time performance. According to the shortcomings of the application, the block partition technique and wavelet transformation were used to change the system state equation described in timedomain into block state equation. Then,the real-time measurement vector was expressed in the form of block state equation. At last, an improved multi-scale filtering method of multi-sensor integrated navigation system was established using Kalman filter and sequential filter. The algorithm was applied to the GPS/SST/SINS multisensor integrated navigation system, and the simulation results show that this algorithm has not only better realtime and recursive performance, but also better fused precision.

Key words: multi-scale filter, improved algorithm, Kalman filter, integrated navigation system, block state equation

LIN Xueyuan, SUN Yumei, DONG Yunyun, QIAO Yuxin, CHEN Xiangguang. Improved multiscale filtering algorithm of multisensor integrated navigation system#br#[J]. Chinese Space Science and Technology, 2020, 40(4): 61-68.

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URL: http://journal26.magtechjournal.com/kjkxjs/EN/10.16708/j.cnki.1000-758X.2020.0046

http://journal26.magtechjournal.com/kjkxjs/EN/Y2020/V40/I4/61

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Improved multiscale filtering algorithm of multisensor integrated navigation system#br#

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