Comparative Analysis of Non Linear Estimation Schemes used for Undersea Sonar Applications

Abstract

    The performance evaluation of various passive underwater target tracking algorithms like Pseudo Linear Estimator, Maximum Likelihood Estimator, Modified Gain Bearings-only Extended Kalman Filter, Unscented Kalman Filter, Parameterized Modified Gain Bearings-only Extended Kalman Filter and Particle Filter coupled with Modified Gain Bearings-only Extended Kalman Filter using bearings-only measurements is carried out with various scenarios in Monte Carlo Simulation. The performance of Parameterized Modified Gain Bearings-only Extended Kalman Filter is found to be better than all estimates.