Chinese Space Science and Technology ›› 2020, Vol. 40 ›› Issue (4): 61-68.doi: 10.16708/j.cnki.1000-758X.2020.0046

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

LIN Xueyuan, SUN Yumei, DONG Yunyun, QIAO Yuxin, CHEN Xiangguang   

  1. 1 Department of Electrical and Electronic Engineering,Yantai Nanshan University,Yantai265713,China
    2 Beijing Institute of Technology,Beijing100081,China

  • Online:2020-08-25 Published:2020-07-20

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