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

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. The algorithm is illustrated via a simulation example involving tracking of two highly maneuvering, at times closely spaced, targets.