Source Code for Radar Tracking Using Kalman Filter Implementation in MATLAB

This document provides a MATLAB-implemented source code for radar tracking using Kalman filtering. The program is based on the Kalman filter algorithm and serves as a practical tool to facilitate target tracking operations. The Kalman filter algorithm employs a Bayesian estimation approach that predicts future target positions by combining previous observations with current measurements. The implementation includes key MATLAB functions for state prediction (predicting target position and velocity) and measurement update (correcting predictions with sensor data). The code structure demonstrates proper handling of covariance matrices and gain calculations essential for optimal filtering performance. This program can be effectively utilized in real-world applications such as automotive navigation systems, aerospace tracking, and robotics. For those interested in Kalman filtering algorithms and radar tracking methodologies, this implementation offers an excellent learning resource and practical implementation example, featuring commented code sections that explain matrix operations and recursive estimation processes.