Tracking of two targets in clutter with possibly unresolved measurements

We present a (suboptimal) filtering algorithm for tracking highly maneuvering targets in a cluttered environment using multiple sensors. We concentrate on two targets which temporarily move in close formation, giving rise to a single detection due to the resolution limitations of the sensor. The filtering algorithm is developed by applying the basic interacting multiple model (IMM) approach and a joint probabilistic data association with merged measurements (JPDAM) technique and coupled target state estimation to a Markovian switching system. The algorithm is illustrated via two simulation examples. Compared with an existing IMM/JPDA (joint probabilistic data association) filtering algorithm developed without accounting for merged measurements, the proposed algorithm achieves significant improvement in both the accuracy of track estimation during target merging period and the number of lost tracks.