Multisensor tracking of multiple maneuvering targets in clutter using IMM/JPDA fixed-lag smoothing

Abstract

Presents a suboptimal fixed-lag smoothing algorithm for tracking multiple maneuvering targets in clutter using multiple sensors and switching multiple target motion models. The fixed-lag smoothing algorithm is developed by applying the basic interacting multiple model (IMM) approach and joint probabilistic data association (JPDA) technique to a state-augmented system. The algorithm is illustrated via a simulation example. Compared to the IMM/JPDA filtering algorithm, the proposed smoothing algorithm achieves significant improvement in the accuracy of track estimation by introducing a small time lag between the instants of estimation and latest measurements whereas the computational load for target state estimation increases linearly with lag and that for data association remains the same.