Radar Multi-Target Maneuvering Tracking

In radar multi-target maneuvering tracking, we can utilize the IMM (Interactive Multiple Model) approach to achieve enhanced tracking performance. By employing different filtering algorithms such as UKF (Unscented Kalman Filter) and EKF (Extended Kalman Filter), we can further optimize tracking accuracy. Below is the program listing with implementation details: - CAEKF.m: Implements EKF filtering using the Constant Acceleration (CA) model, which handles target motion with constant acceleration assumptions - IMMUKF.m: The main Interactive Multiple Model UKF filtering program that manages multiple model interactions for better maneuvering target tracking - FX1.m: System equation function for the Constant Velocity (CV) model within IMMUKF.m, defining the state transition for non-accelerating targets - FX2.m: System equation function for the Constant Acceleration (CA) model within IMMUKF.m, handling state propagation for accelerating targets - FZ.m: Observation equation function for IMMUKF.m, defining the measurement model that maps target states to radar observations Additionally, we provide the following data files for testing and validation: - Measure.mat: Contains observation data collected from radar measurements - Real.mat: Includes ground truth data for performance evaluation and comparison These programs and datasets facilitate comprehensive understanding of radar multi-target maneuvering tracking principles and their practical implementation, demonstrating how multiple models interact to handle target maneuvers effectively.