MATLAB Source Code for UKF, EKF, and IMM Algorithms

International scholars have developed high-quality MATLAB source code implementations for UKF (Unscented Kalman Filter), EKF (Extended Kalman Filter), and IMM (Interacting Multiple Model) algorithms. These implementations feature:

Clear annotations: The source code contains comprehensive comments explaining the implementation logic of key steps, making it easy to understand and modify. The code includes detailed explanations of sigma point selection in UKF, Jacobian matrix calculations in EKF, and model probability updates in IMM.

Strong organization: The code follows a modular structure with standardized function and variable naming conventions, facilitating integration into other projects or research studies. Key functions are organized separately for prediction, update, and model interaction phases.

Complete documentation: Accompanied by technical documentation covering algorithm principles, usage methods, and simulation examples suitable for users at different proficiency levels. The documentation includes mathematical derivations and practical implementation considerations.

Latest version optimization: The code undergoes continuous updates to improve computational efficiency and numerical stability, making it suitable for applications such as target tracking and navigation systems. Recent versions feature memory optimization and parallel processing capabilities.

These resources are typically available on open-source platforms (such as GitHub) or as supplementary materials in academic papers, serving as practical references for researching nonlinear filtering and multi-model estimation techniques.