IMM Interactive Multiple Model MATLAB Algorithm Implementation

Our Interactive Multiple Model MATLAB implementation incorporates left-turn, right-turn, and constant velocity motion models, employing Kalman filtering for predictive estimation to significantly enhance tracking accuracy and stability. The algorithm maintains multiple model filters running in parallel, with probabilistic weighting based on model likelihoods and transition probabilities. To facilitate comprehensive performance analysis, we provide multiple error evaluation metrics including RMSE and NEES, along with visualization tools for trajectory comparisons and innovation analysis. The implementation is particularly suitable for target tracking applications where the state space consists of position and velocity components, enabling robust motion target tracking in dynamic environments. Key code components include model transition probability matrices update functions, Kalman filter prediction-correction cycles, and interactive mixing of model-conditioned estimates. The package contains essential files for motion target tracking, model probability updates, and Kalman filter implementations, providing clear insights into the algorithm workflow and results. We hope this information helps you better understand our Interactive Multiple Model MATLAB implementation. For any questions or suggestions, please feel free to contact us.