Optimal Maneuver Strategy of Observer for Bearing-Only Tracking in Threat Environment

Abstract

The optimal maneuver of observer for bearing-only tracking (BOT) in a threat environment is a complex problem which involves nonlinear filtering, threat avoidance, and optimal maneuver strategy. Under comprehensive consideration, the reward function comprised of the lower bound on detFIM and threat cost was established; the finite-horizon MDP principle was applied to obtain the optimal strategy. The quantization method was used to discretize the BOT process and calculate the transition matrix of Markov chain; to achieve quantization in the beginning of each period, CKF was applied to provide the initial state estimate and the corresponding error covariance. The numerical simulations illustrated the applicability and superior performance for static and dynamic target tracking in several scenarios in the threat environment.