MATLAB Implementation of the Unscented Kalman Filter (UKF) Algorithm

In this article, I introduce the Unscented Kalman Filter (UKF) algorithm and share my personal implementation experience. Having utilized this algorithm extensively across multiple projects, I have developed deep familiarity with its mechanics. In my practical applications, the UKF algorithm has proven to be an invaluable tool for solving various state estimation problems involving nonlinear systems. My implementation employs the standard unscented transformation approach with carefully tuned parameters for sigma point generation and weight calculation. The code structure maintains clear separation between prediction and update phases, with well-documented functions handling state transition, measurement models, and covariance propagation. I believe this article will provide valuable insights for readers seeking to understand and implement UKF filtering algorithms. Furthermore, I maintain consistent coding standards throughout the implementation to ensure clarity and readability, including proper variable naming conventions, comprehensive comments, and modular function design that facilitates easy customization and debugging.