Underwater Target Tracking by Bearing-Only Measurements Using Robust Fifth-Degree Cubature Kalman Filter in Presence of Outliers

Target tracking by bearing-only measurements is one of the main methods for passive tracking of underwater moving targets. In this problem, the choice of filter type and accuracy of estimates from target state variables have always been the most important topics, but in many cases and applications of this kind of tracking, the presence of outliers in the measurements are unavoidable which reduce the accuracy of estimates or stability in the performance of the tracking filters. In this paper, to overcome this problem, a new method based on a robust M-estimation in fifth-degree cubature Kalman filter structure is presented. In this method, the outlier in the measurement is detected, and the weight of this malicious data is reduced using Huber's weight function. Analysis of the underwater target tracking problem are discussed in three situations: without the presence of outliers, the presence of small outliers in some continuous measurements and the presence of large outliers. This analysis indicates the effectiveness of the proposed method so that the accuracy of the estimates made by the selected filter is still at an acceptable level.