Distributed multi-target tracking with Y-shaped passive linear array sonars for effective ghost track elimination

Abstract

Y-shaped passive linear array sonar (PLAS) systems are composed of three sensor legs that independently report bearings-only measurements with bearing-ambiguity. Given that many ghost targets are generated due to the bearing-ambiguity, multi-target tracking using a PLAS system is a challenging problem, especially when target miss-detection and clutter are also considered. Centralized methods in most cases can obtain good tracking performances. However, they suffer from heavy communicational burdens and computational loads, as all measurements generated by all sensors are sent to the fusion center (FC). To reduce the communicational and computational burdens, a distributed target tracking method is proposed. In this method, to reduce the numbers of false tracks and ghost tracks, the original bearings-only measurements are temporarily tracked without considering the bearing-ambiguity at each local PLAS using a linear multi-target integrated probabilistic data association (LM-IPDA) tracker, which can handle false track discrimination (FTD). Then, the estimated bearings-only measurements from each local tracker are transmitted to the FC, where multiple targets are tracked using the sequential LM-IPDA while considering the bearing-ambiguity problem. To further reduce the number of false tracks generated by the bearing-ambiguity, a novel measurement-to-track assignment method is proposed for the distributed tracking method. Simulations show that the proposed methods have high tracking accuracies, as well as fewer communicational and computational loads, for multi-target tracking with the Y-shaped PLAS system.