A Novel Single Observer Passive Localization Method Based on MOEA

A novel single observer passive localization method using DOA and TDOA based on Multi-objective Evolutionary Algorithm (MOEA) is presented, which avoids the drawback of traditional methods. Moreover, a simple and effective decision-making strategy for MOEA is designed. Experiments validate that without initialized estimate and linearization processing, the proposed method is steadily able to achieve a localization accuracy with small difference from Cramer-Rao Lower Bound (CRLB) under the condition of single observation. Finally, a conclusion can be drawn that solving passive localization problem from the perspective of multi-objective optimization is practicable.