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Ant colony optimization for bearings-only maneuvering target tracking in sensors network
引用本文:Benlian XU,Zhiquan WANG,Zhengyi WU. Ant colony optimization for bearings-only maneuvering target tracking in sensors network[J]. 控制理论与应用(英文版), 2007, 5(3): 301-306. DOI: 10.1007/s11768-005-5190-9
作者姓名:Benlian XU  Zhiquan WANG  Zhengyi WU
作者单位:[1]Department of Information and Control Engineering, Changshu Institute of Technology, Changshu Jiangsu 215500, China; [2]School of Automation, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China
基金项目:This paper was supported by the Natural Science Foundation of Jiangsu province of China (BK2004132).
摘    要:In this paper, the problem of bearings-only maneuvering target tracking in sensors network is investigated. Two objectives are proposed and optimized by the ant colony optimization (ACO), then two kinds of node searching strategies of the ACO algorithm are presented. On the basis of the nodes determined by the ACO algorithm, the interacting multiple models extended Kalman filter (IMMEKF) for the multi-sensor bearings-only maneuvering target tracking is introduced. Simulation results indicate that the proposed ACO algorithm performs better than the Closest Nodes method. Furthermore, the Strategy 2 of the two given strategies is preferred in terms of the requirement of real time.

关 键 词:蚁群算法 多目标最优化 机动目标跟踪 传感器网络
收稿时间:2005-07-25
修稿时间:2005-07-25

Ant colony optimization for bearings-only maneuvering target tracking in sensors network
Benlian XU,Zhiquan WANG,Zhengyi WU. Ant colony optimization for bearings-only maneuvering target tracking in sensors network[J]. Journal of Control Theory and Applications, 2007, 5(3): 301-306. DOI: 10.1007/s11768-005-5190-9
Authors:Benlian XU  Zhiquan WANG  Zhengyi WU
Affiliation:1. Department of Information and Control Engineering, Changshu Institute of Technology, Changshu Jiangsu 215500, China; School of Automation, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China
2. School of Automation, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China
3. Department of Information and Control Engineering, Changshu Institute of Technology, Changshu Jiangsu 215500, China
Abstract:In this paper, the problem of bearings-only maneuvering target tracking in sensors network is investigated. Two objectives are proposed and optimized by the ant colony optimization (ACO), then two kinds of node searching strategies of the ACO algorithm are presented. On the basis of the nodes determined by the ACO algorithm, the interacting multiple models extended Kalman filter (IMMEKF) for the multi-sensor bearings-only maneuvering target tracking is introduced. Simulation results indicate that the proposed ACO algorithm performs better than the Closest Nodes method. Furthermore, the Strategy 2 of the two given strategies is preferred in terms of the requirement of real time.
Keywords:Ant colony algorithm   Multi-objective optimization   Maneuvering target tracking   Bearings-only
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