Extended Kalman Filter Algorithm Source Code

In this article, we present the source code for an Extended Kalman Filter (EKF) algorithm. The Extended Kalman Filter is a state estimation technique designed for nonlinear systems. Unlike the traditional Kalman Filter, the EKF effectively handles nonlinearities through linearization of the system model around the current state estimate. The provided source code is straightforward to comprehend while maintaining robust functionality. We will thoroughly explain the algorithm's principles, including state prediction and measurement update steps with Jacobian matrix calculations for linearization. Additionally, we demonstrate how to implement state estimation using this algorithm with practical code examples featuring key functions like state transition modeling and covariance propagation. These implementations will help readers better understand the EKF's practical application. We are confident that this article will enable readers to grasp the Extended Kalman Filter algorithm comprehensively and apply it effectively to real-world problems.