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集中交互式多传感器联合概率数据互联算法
  • ISSN号:1003-501X
  • 期刊名称:《光电工程》
  • 时间:0
  • 分类:TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]海军航空工程学院信息融合技术研究所,山东烟台264001
  • 相关基金:国家自然科学基金(60172033),全国优秀博士论文作者专项资金(200036),高校骨干教师资金(3240)
中文摘要:

为了解决杂波环境下多传感器多机动目标跟踪问题,本文提出了一种集中交互式多传感器联合概率数据互联算法。本文提出的算法首先应用广义S—D分配的规则对每个传感器送来的观测数据进行排列组合,并对所有的测量组合进行有效性判断,然后应用数据压缩的方法将每个有效量测组合压缩成一个等效量测点并根据每个等效量测点的联合似然函数计算其联合互联概率,最后在此基础上应用交互式多模型算法的思想以处理目标出现机动的问题。本文最后给出了该算法的分析,仿真结果表明,本文算法能够很好地解决杂波环境下多传感器多机动目标的跟踪问题。

英文摘要:

In order to resolve the problem of tracking multiple maneuvering targets in centralized multi-sensor situation, a new centralized interacted multi-sensor joint probabilistic data association (CIMM-MSJPDA) algorithm is presented, which is a combination of centralized Multi-sensor Joint Probabilistic Data Association (MSJPDA) techniques and Interacted Multiplied Model (IMM) method. The algorithm is proposed to associate measurements from each sensor with the target from which the measurements originated by use of MSJPDA techniques, and to track maneuvering targets with IMM method In the new algorithm, the measurements from each sensor are permuted and combined, and some combinations will be accepted according to a rule. Then, all of the measurements in each combination accepted will be compacted into an equivalent measurement which is associated with targets by using the MSJPDA techniques. Finally, the interacted multiple model method is applied to resolve the maneuvering target tracking problem. Simulations are designed to compare the performance of the new algorithm with a centralized MSJPDA method and IMMJPDA algorithm. The results show that the use of CIMM-MSJPDA algorithm enables the centralized multi-sensor system track multiplied maneuvering targets and its tracking performance is much better than that of IMMJPDA algorithm.

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期刊信息
  • 《光电工程》
  • 中国科技核心期刊
  • 主管单位:中国科学院
  • 主办单位:中国科学院光电技术研究所 中国光学学会
  • 主编:罗先刚
  • 地址:四川省成都市双流350信箱
  • 邮编:610209
  • 邮箱:oee@ioe.ac.cn
  • 电话:028-85100579
  • 国际标准刊号:ISSN:1003-501X
  • 国内统一刊号:ISSN:51-1346/O4
  • 邮发代号:62-296
  • 获奖情况:
  • 四川省第二次期刊质量考评自然科学期刊学术类质量...,四川省第二届优秀期刊评选科技类期刊三等奖
  • 国内外数据库收录:
  • 美国化学文摘(网络版),荷兰文摘与引文数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:14003