电子学报 ›› 2012, Vol. 40 ›› Issue (11): 2200-2205.DOI: 10.3969/j.issn.0372-2112.2012.11.010

• 学术论文 • 上一篇    下一篇

一种异步航迹关联的变异蚁群算法

郭蕴华, 袁成   

  1. 1. 武汉理工大学能源与动力工程学院,湖北武汉 430063;
    2. 船舶动力工程技术交通行业重点实验室,湖北武汉 430063
  • 收稿日期:2010-11-29 修回日期:2012-09-10 出版日期:2012-11-25
    • 通讯作者:
    • 郭蕴华 男,1975年6月出生,四川省成都人.武汉理工大学能源与动力工程学院副教授,工学博士.已发表论文十余篇,其中被EI收录5篇.获省部级一等奖1项、二等奖3项.主要研究方向为信息融合、分布式系统仿真等. E-mail:wtugyh@163.com
    • 作者简介:
    • 袁 成 男,1986年12月出生,湖北省潜江人.武汉理工大学能源与动力工程学院硕士研究生.主要研究方向为故障预测与诊断、信息融合等.
    • 基金资助:
    • 国家自然科学基金 (No:50979085); 中央高校基本科研业务费专项资金 (No:123205001)

A Mutation Ant Colony Algorithm for the Asynchronous Track Correlation

GUO Yun-hua, YUAN Cheng   

  1. 1. School of Energy and Power Engineering,Wuhan University of Technology,Wuhan,Hubei 430063,China;
    2. Key Lab.of Marine Power Engineering and Technology Under Ministry of Communications of China, Wuhan University of Technology,Wuhan,Hubei 430063,China
  • Received:2010-11-29 Revised:2012-09-10 Online:2012-11-25 Published:2012-11-25
    • Supported by:
    • National Natural Science Foundation of China (No:50979085); Fundamental Research Funds for the Central Universities (No:123205001)

摘要: 本文提出了一种异步多传感器航迹关联的变异蚁群算法.该算法基于最优预测公式实现异步航迹的时间同步,通过动态删除可访问节点索引以规避不可行解,对最优关联结果进行变异操作以提高收敛速度和降低求解时间,采用非均匀的初始信息素分布策略以减少无效分配.仿真结果表明,本文提出的算法计算代价较小,并且具有较高的正确关联率.

关键词: 异步航迹关联, 多维分配, 蚁群算法, 变异

Abstract: A mutation ant colony algorithm for the asynchronous muti-sensor track correlation is proposed.The time synchronization of the asynchronous tracks is implemented by optimal prediction.The infeasible solutions is avoided by dynamically deleting the index of the accessible nodes.The mutation operations for the optimal result is employed to elevate convergent speed and reduce the solving time.A non-uniformly distributional strategy of the initial pheromones is adopted to reduce the invalid assignments.The simulation results show that the computational cost of the algorithm is small and its correct percent of track correlation is iigh.

Key words: asynchronous track correlation, multi-dimention assignment, ant colony algorithm, mutation

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