Maneuvering Target Tracking Approaches Based on Turning Rate Estimation

A new class of interacting multiple-model algorithms based on turning rate estimation for maneuvering target tracking is presented. To track turning maneuver, the key is how to estimate the parameter of motion, i.e., target's turning rate. It can be obtained in real time while the target's heading is filtered using multiple motion models, which include current statistical model and constant angular velocity model. Then the result estimated could be integrated with the variation of circular-turn model (VCTM) and the curvilinear model (CM), referred to as modified VCTM (MVCTM) and modified CM (MCM) respectively. The performances of the algorithms presented here are evaluated and compared via simulation of a generic maneuvering target tracking problem. Simulation results show that the MVCTM-based significantly outperform the MCM-based tracker.