A tracker-aware detector threshold optimization formulation for tracking maneuvering targets in clutter

In this paper, we consider a tracker-aware radar detector threshold optimization formulation for tracking maneuvering targets in clutter. The formulation results in an online method with improved transient performance. In our earlier works, the problem was considered in the context of the probabilistic data association filter (PDAF) for non-maneuvering targets. In the present study, we extend the ideas in the PDAF formulation to the multiple model (MM) filtering structures which use PDAFs as modules. Although our results are general for the MM filters, our simulation experiments apply the proposed solution in particular for the interacting multiple model PDAF (IMM-PDAF) case. It is demonstrated that the suggested formulation and the resulting optimization method exhibits notable improvement in transient performance in the form of track loss immunity. We believe the method is promising as a detector-tracker jointly-optimal filter for the IMM-PDAF structure for tracking maneuvering targets in clutter.

► A method for optimization of detection thresholds for maneuvering target tracking is proposed. ► The method is fully integrated into MM filtering structures which use the PDAFs as modules. ► The solution utilizes the soft model switching mechanism inherently available in MM filtering. ► The formulation results in an on-line method with improved track-loss performance.