首页|Fault-tolerant SINS/HSB/DVL underwater integrated navigation system based on variational Bayesian robust adaptive Kalman filter and adaptive information sharing factor
Fault-tolerant SINS/HSB/DVL underwater integrated navigation system based on variational Bayesian robust adaptive Kalman filter and adaptive information sharing factor
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
? 2022 Elsevier LtdTo solve the problem that position information obtained by SINS/DVL integrated navigation system is divergent in the underwater navigation applications, this paper introduces hydroacoustic single beacon (HSB) into the underwater integrated system and proposes a novel SINS/HSB/DVL fault-tolerant federated variational Bayesian robust adaptive Kalman filter (FVBRAKF). In the FVBRAKF, the traditional KF is replaced by VBRAKF, which not only suppress the adverse influence of outliers based on Mahalanobis distance (MD) effectively, but also estimate the unknown measurement noise covariance based on variational Bayesian (VB) approximation adaptively. Meanwhile, a novel adaptive information sharing factor (ISF) method is proposed during the information fusion process to form an improved FVBRAKF（IFVBRAKF）, which can adjust the fusion weights in real-time according to the accuracy of local filter. The semi-physical simulation experiments for SINS/HSB/DVL underwater integrated navigation system based on the test data are carried out to verify the adaptive ability of the ISF and the robust adaptive ability of the method, respectively. Experimental results demonstrate that the proposed algorithm can not only improve the estimation accuracy, but also enhance the fault-tolerant performance.
Federated Kalman filterInformation sharing factorSINS/HSB/DVLUnderwater integrated navigation system
Shi W.、Xu J.、He H.、Tang H.、Lin E.、Li D.
展开 >
College of Electrical Engineering Naval University of Engineering
College of Advanced Interisciplinary Studies National University of Defense Technology
NSTL
Elsevier
