Kalman Filter Simulation Program Collection

In this article, we present various simulation programs related to Kalman filtering, designed to help you better understand and master the principles and applications of Kalman filters. These simulations demonstrate different implementation approaches including standard Kalman filter algorithms, extended Kalman filters (EKF) for nonlinear systems, and unscented Kalman filters (UKF) for more complex scenarios. The programs utilize diverse datasets and parameter configurations, allowing you to comprehensively analyze Kalman filter performance characteristics and limitations under various conditions. Key functions implemented include state prediction, measurement update, covariance matrix calculations, and innovation sequence processing. Additionally, we provide relevant theoretical background and reference materials to facilitate deeper understanding of Kalman filter mathematical foundations and practical applications. Each simulation includes comments explaining the algorithmic steps and parameter tuning considerations. We hope these resources will enhance your learning experience with Kalman filtering and provide valuable support for your research and professional work.