Ground moving target tracking using signal strength measurements with the GM-CPHD filter

In ground target tracking based on kinematic measurements by airborne radar, several challenges in general strongly deteriorate the performance of any standard tracking filter. The major challenges are imprecise measurements and missed detections, a strong false alarm background, closely-spaced targets, technical and terrain obscuration, and complex target motion. In order to counterbalance such a performance degradation, target attribute and context information can be incorporated into the tracking process. One such target attribute information is provided by the signal strength measurement, which is readily available as it is a standard output of a modern radar system. Signal strength information can be used to estimate the radar cross section (RCS) of a ground moving target. For this method to work, the fluctuations of the target RCS are assumed to follow the analytically tractable Swerling-I and Swerling-III cases. In the present work, the RCS estimation scheme is implemented into the Gaussian mixture cardinalized probability hypothesis density (GM-CPHD) filter. The performance of the resulting algorithm is then analyzed based on single and multiple-target simulation scenarios.