Performance Analysis of Extended Kalman filter and Unscented Kalman filter for Doppler Bearing Passive Target Tracking

Abstract-Conventional passive bearing together with Doppler measurements is explored in Target motion analysis (TMA). This Doppler bearing tracking (DBT) approach offers one advantage compared to bearings-only tracking, that DBT does not require ownship maneuver. By using EKF and unscented Kalman filter (UKF), the target motion analysis is carried out. To obtain the convergence of the estimation fast the inclusion of range and bearing parameters is proposed in the target state vector. Doppler shifts are experienced by the harmonic signals at the ownship so that the frequency measurements can be explored to improve estimation accuracy. This paper deals with the performance evaluation of both EKF and UKF for under water tracking applications and the results for DBT are compared between extended Kalman filter and Doppler-bearing passive target tracking using unscented Kalman filter Monte Carlo simulations