AN INNOVATIVE APPROACH TO MORE RELIABLE AND AUTOMATED TARGET CLASSIFICATION FOR UNDERWATER MARITIME SURVEILLANCE

Abstract

Target motion analysis (TMA) using conventional passive bearing together with frequency measurements is explored. This approach offers one tactical advantage over the classical bearings-only TMA. It makes the ownship maneuver superfluous. In this paper, TMA is carried out using Unscented Kalman Filter (UKF). Inclusion of range, course and speed parameterization is proposed in UKF target state vector to obtain the convergence of the solution fast. Finally the results of various scenarios in Monte-Carlo simulation are presented.