Implementation and Analysis of Various Kalman Filtering Techniques for Target Tracking

Abstract

RADAR plays a crucial role in target tracking. A faulty tracking is vulnerable to fatal errors. Since RADAR signals contain noise in them, filters are used to remove the noise. This paper implements Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Cubature Kalman Filter (CKF) for radar target tracking. Each filter is exposed to the same environment and the results are observed. A radar target tracking model is proposed with an input chirp signal of 77 GHz. The turn rate is varied between 0.2 and 150. The simulations are carried out in MATLAB. Since every simulation generates random motions of the target, the filter can be gauged only on the basis of how well the estimated trajectory follows the true trajectory. The findings have shown that EKF works best for large turn rate and high noise, in comparison to UKF and CKF, thus making it an appropriate choice for such applications.