航姿参考系统中一种自适应卡尔曼滤波算法

doi:10.3969/j.issn.1001-2400.2011.06.016

Abstract

Abstract:

Due to the uncertainty of measurement noise, the accuracy of the Kalman filter is affected seriously while measuring the vehicle attitude in the Attitude and Heading Reference System(AHRS). The sudden change of measurement noise brought by interference of the system even leads to filter divergence. An algorithm for the adaptive Kalman Filter used in AHRS is presented in this paper, which is able to estimate the measurement noise in real time according to observation data and improve the accuracy of the Kalman Filter. Simulation result shows that the results of the Kalman filter diverge clearly even though the measurement noise varies, and that the adaptive Kalman filter results converge very well. The system stability is markedly improved without significant increase in computing complexity.

Key words: attitude and heading reference system, adaptive filter, Kalman filter, fuzzy control

CLC Number:

V241.62

TIAN Yi;SUN Jinhai;LI Jinhai;YAN Yuepeng. Algorithm for the adaptive Kalman filter in AHRS[J].J4, 2011, 38(6): 103-107+122.

References

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Algorithm for the adaptive Kalman filter in AHRS

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