A Novel Single Observer Passive Localization Method Based on MOEA

摘要：

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.

关键词： passive localization multi-objective optimization (MOP) multi-objective evolutionary algorithm (MOEA) NSGAII Cramer-Rao Lower Bound(CRLB)

作者: Fei Tong Jun Wang Hong-wei Li Li-zheng Zhang Chun-juan He

作者单位: National lab of Radar Signal Processing,Xidian University,Xian,China

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 913-916

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）