Multiple Underwater Target Bearing Tracking Using Member Filter

Abstract

Underwater acoustic vector sensors (AVS) are devices which can measure scalar pressure and three dimensional acceleration or particle velocity with only one sensor. By using these four measurements, target detection and tracking is possible. In case multiple targets exist, multi-target detection and tracking methods must be applied. Because these methods are more general, the algorithms are more involved and complex. In this framework, multi-target multi-Bernoulli (MeMBer) is a promising filter based on random finite sets (RFS) for multi-target tracking problems. In this work, for the first time in the literature, MeMBer filter is analyzed using a single underwater acoustic vector sensor in a scenario including two targets. Simulation results indicate that MeMBer filter can successfully track the targets.