Parametric Concomitant Search Based on IMM-ACT Maneuvering Target Tracking Algorithm

The existing Interacting Multiple Model (IMM) algorithm encounters issues such as model switching lag and increased filtering errors when tracking maneuvering targets, particularly in scenarios involving frequent target turns. To address these challenges, this paper proposes an Adaptive Coordinated Turn-Interacting Multiple Model (IMM-ACT) maneuvering target tracking algorithm based on parameter-concomitant search. The algorithm employs a parameter-concomitant randomized search to generate multiple parallel ACT sub-model filters, which adaptively estimate the current target’s turning parameters to form the main model filter in real-time. By effectively covering changes in the target’s motion patterns, the proposed algorithm captures rapid transitions in target motion. Simulation results demonstrate that the IMM-ACT algorithm identifies changes in target motion patterns more quickly and accurately than existing algorithms, thereby significantly improving the accuracy of target tracking.