Estimation of LOS Rates for Target Tracking Problems using EKF and UKF Algorithms- a Comparative Study

One of the most important problem in target tracking is Line Of Sight (LOS) rate estimation for using from PN (proportional navigation) guidance law. This paper deals on estimation of position and LOS rates of target with respect to the pursuer from available noisy RF seeker and tracker measurements. Due to many important for exact estimation on tracking problems must target position and Line Of Sight rates estimated with least error rather than actual values. In this paper extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithms are used for estimation of target position in three-dimensional (3-D) and LOS rates in elevation and azimuth for seekers and trackers. For comparison of algorithms, model of the system simulated using MATLAB and many tests were carried out. Simulation experiments show that the efficiency of EKF due to least RMSE has better performance. However, the performance of EKF algorithm has been dramatically decreased when initializations (initial state assumption) are not near to real values, which in this condition UKF method provides a more accurate approximation. Numerical results from simulations show that the UKF is robust against uncertainties and has better state estimation accuracy. Therefore, UKF algorithm is appropriate, and it can run on target tracking systems