Interactive Multi-Model UKF and EKF Filtering Program in MATLAB

In the text you provided, we identified a brief description and will therefore expand it with additional details to enhance reader comprehension. We recommend including the following information when introducing the MATLAB interactive multi-model UKF and EKF filtering program: - First, provide detailed explanations of the program's applications, including which domains utilize this technology and why it's significant for handling systems with multiple dynamic models. The program implements Interacting Multiple Model (IMM) algorithm combined with Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) for superior tracking performance in maneuvering target scenarios. - Second, discuss the program's design and development process, including how the code architecture was structured, testing methodologies employed, and any challenges encountered during implementation. The development involved creating modular functions for model probability calculation, state mixing, and filter interaction, with validation through Monte Carlo simulations. - Finally, provide comprehensive details about program usage and implementation, including installation requirements, configuration parameters, and interpretation of output results. The program features interactive GUI components for real-time parameter adjustment and visualization of filtering performance metrics. These detailed specifications will help readers better understand the MATLAB interactive multi-model UKF and EKF filtering program and how to utilize it effectively. Furthermore, we recommend incorporating these details in the accompanying documentation for future reference. Thank you!