| Citation: | JIN K D，CHAI H Z，SU C H，et al. Fading memory variational Bayesian adaptive filter based on variable attenuating factor[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（11）：2989-2999 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0799
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The measurement noise for global navigation satellite system/strapdown inertial navigation system (GNSS/SINS) suffers from abrupt changes due to the easy interference of GNSS signals. In this paper, a novel fading memory variational Bayesian adaptive Kalman filter (VBAKF) with variable attenuating factors is proposed to estimate the abrupt measurement noise for GNSS/SINS system. The Chi-square detection method is reconstructed by initial standard deviation of GNSS noise. The hyperparameter transfer structure of VBAKF is then transformed into the error covariance matrix correction structure, and a novel variable memorial factor function is established to dynamically adjust the attenuating factor in VBAKF. Experimental results show that the proposed algorithm can adaptively estimate the abrupt measurement noise, and that the position accuracy of GNSS/SINS is improved in the presence of abrupt noise.
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