Multisensor tracking of a manoeuvring target in clutter using IMMPDA fixed-lag smoothing

We present a suboptimal fixed-lag smoothing algorithm for tracking a highly manoeuvring target in a cluttered environment using multiple sensors. The fixed-lag smoothing algorithm is developed by applying the basic interacting multiple model (IMM) approach and the probabilistic data association (PDA) technique to a state-augmented system. The algorithm is illustrated via a simulation example. Compared with an existing IMMPDA 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 increases linearly with lag