Kalman Filter

As mentioned in this article, the Kalman Filter is an "optimal recursive data processing algorithm" designed to solve a wide array of problems. Due to its efficiency and practicality, it has been widely applied in fields such as robotic navigation, control systems, and sensor data fusion. Additionally, the Kalman Filter has been utilized in military radar systems and missile tracking for over 30 years. In recent years, with advancements in computer technology, it has also found applications in computer image processing, including facial recognition, image segmentation, and edge detection. It is worth noting that the Kalman Filter is not only valuable for practical applications but also receives significant attention in academic research due to its utility in solving real-world problems. The algorithm's core implementation involves state-space modeling with recursive Bayesian filtering, where key functions handle prediction updates using system dynamics and measurement updates incorporating sensor observations with noise covariance matrices.