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被动传感器系统模糊-概率双加权数据关联新算法
引用本文:李良群,姬红兵,刘进忙. 被动传感器系统模糊-概率双加权数据关联新算法[J]. 系统仿真学报, 2006, 18(10): 2898-2902
作者姓名:李良群  姬红兵  刘进忙
作者单位:1. 西安电子科技大学电子工程学院,西安,710071
2. 西安电子科技大学电子工程学院,西安,710071;空军工程大学导弹学院,陕西,三原,713800
摘    要:针对被动传感器系统中的数据关联问题,提出了一种新的被动传感器系统模糊-概率双加权数据关联算法。该算法首先利用候选关联的方位角建立检验统计量,进行方位的粗关联,排除一部分虚假候选关联,减少计算量;再对保留的候选关联进行交叉定位,计算每个交叉定位点与各个目标的关联概率;同时对相应的候选关联建立模糊关联度,来修正目标的关联概率,最后采用最大值搜索方法得到各个目标的正确关联。仿真结果表明,该方法可以快速、准确的排除虚假定位点,能够有效的对多个目标进行跟踪。

关 键 词:被动传感器系统  数据关联  交叉定位  模糊关联度
文章编号:1004-731X(2006)10-2898-05
收稿时间:2005-08-01
修稿时间:2005-11-28

New Fuzzy-probability Weighting Data Association Algorithm in Passive Sensor System
LI Liang-qun,JI Hong-bing,LIU Jin-mang. New Fuzzy-probability Weighting Data Association Algorithm in Passive Sensor System[J]. Journal of System Simulation, 2006, 18(10): 2898-2902
Authors:LI Liang-qun  JI Hong-bing  LIU Jin-mang
Abstract:For the data association problem in the passive sensor system, a new fuzzy-probability weighting data association algorithm was proposed. Firstly, in order to reduce the computational load, the algorithm made use of the azimuth of the candidate association to construct the statistic test, and use it to eliminate some false candidate associations. Then the candidate associations of the targets were used to estimate the intersection location points by the least square algorithm, and the association probabilities between the targets and the intersection location points were computed. At the same time, the fuzzy relationship degrees of the corresponding candidate associations used to modify the association probabilities were built. Finally, the correct association could be found by the maximum search method. The simulation results show that the proposed algorithm is fast and effective to solve the data association of multiple target tracking.
Keywords:Passive sensor system  Data Association  Cross-Location  Fuzzy Relationship Degree
本文献已被 CNKI 维普 万方数据 等数据库收录!
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