Tracking of multiple maneuvering targets in clutter using multiple sensors, IMM and JPDA coupled filtering

Abstract

Abstract : We consider the problem of tracking multiple maneuvering targets in clutter using switching multiple target motion models. A novel suboptimal filtering algorithm is developed by applying the basic interacting multiple model (IMM) approach, the joint probabilistic data association (JPDA) technique and coupled target state estimation to a Markovian switching system. In past such an approach has been considered using uncoupled target state estimation. The algorithm is illustrated via a simulation example involving tracking of two highly maneuvering, at times closely spaced, targets. In the presented example, the proposed IMM/JPDA coupled filter outperforms an existing IMM/JPDA uncoupled filter.