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RAIM method based on robust extended Kalman filter and extrapolation-accumulation

LI Zhen1, SONG Dan1, ZHANG Pengfei2, XU Chengdong1   

  1. (1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081,China;
    2. College of Mechatronic Engineering, North University of China, Taiyuan 030051,China)
  • Online:2017-08-28 Published:2010-01-03

Abstract:

In order to improve the detection performance of the receiver autonomous integrity monitoring (RAIM) algorithm for micro and slowly growing pseudo-range bias, a new RAIM method based on robust extended Kalman filter (REKF) and extrapolation-accumulation is proposed. In this method, the test statistics of the innovation extrapolation method in several epochs is accumulated, thus it has a better ability in detecting micro and slowly growing bias. Meanwhile, the pseudo-range bias is corrected by REKF. The simulation results show that, compared to the conventional RAIM method, the innovation extrapolation method and the accumulated epoches method, the new method has a higher fault detection rate for micro pseudo-range bias and shorter detection time-delay for slowly growing pseudo-range bias, and the position accuracy is improved after correcting the pseudo-range bias.

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