Bearings-Only Target Motion Analysis via Deep Reinforcement Learning

Abstract

Dear Editor, This letter introduces a novel approach to address the bearings-only target motion analysis (BO-TMA) problem by incorporating deep reinforcement learning (DRL) techniques. Conventional methods often exhibit biases and struggle to achieve accurate results, especially when confronted with high levels of noise. In this letter, we formulate the BO-TMA problem as a Markov decision process (MDP) and process it within a DRL framework. Simulation results demonstrate that the proposed DRL-based estimator achieves reduced bias and lower errors compared to existing estimators.