Ant colony optimization for bearings-only maneuvering target tracking in sensors network
Benlian XU
Zhiquan WANG
Zhengyi WU
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.
机标关键词：maneuvering target trackingant colony optimizationextended Kalman filtermultiple modelsreal time
分类号：TP3(计算技术、计算机技术)
资助基金：江苏省自然科学基金(BK2004132)
论文发表日期：2007-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 301-306 )
英文信息