Research and implementation of the Kalman filter in 3D radar target tracking

Abstract

Tracking a moving target in three-dimensional (3D) space using radar requires the processing system to consistently and accurately update the target's position with minimal delay. The Kalman filter, a powerful tool for target tracking, is utilized to estimate the target's state from noisy measurement data. This paper presents the results of evaluating the effectiveness of the Kalman filter in estimating the altitude and tracking 3D radar targets instead of 2D in existing research. The tests are performed on highly mobile moving target models (UAVs, fighter aircraft, etc.). The evaluation criteria include the accuracy of position and velocity estimation, as well as the computational efficiency of the 3D Kalman filter. Finally, a solution for applying the filter to level 2 processing computers in 3D radar systems is proposed.