Robust Elliptically Contoured Distribution Based Kalman Filter for INS/DVL Integrated Navigation

In complex underwater environment, the outputs of Doppler velocity log (DVL) often contain outliers induced by external disturbance or soft failure, which will degrade the performance of the traditional Kalman filter based INS/DVL integrated navigation system. To address this problem, a novel robust Kalman filter with outlier-contaminated measurement noise modelled as elliptically contoured distributed is proposed. Firstly, an analytical update form of the joint posterior probability density function is derived via introducing an unknown parameter. Then the fixed-point iteration method is exploited to achieve an approximate estimate of the unknown parameter, based on which the required joint posterior probability density function is analytically updated. Finally, simulation results of INS/DVL integrated navigation are used to verify the validity and advantages of the proposed method.