摘要
研究了漏检情况下多传感器多目标检测中的数据关联问题，并将其描述为数学规划中组合最优化问题． 当传感器数大于等于３ 时，该问题的求解是ＮＰ的． 文中提出了一种基于ＧＡ（Ｇｅｎｅｔｉｃ Ａｌｇｏｒｉｔｈｍ） 的数据关联算法，仿真实验表明，该算法具有较高的关联成功率，并能优化求解的目标个数，提高多传感器系统的检测概率．
This paper is concerned with the problem of data association in multisensor multitarget detecting in the presence of missed detections and an unknown number of targets. The data association problem is formulated as a multiple dimensional assignment problem in combinatorial optimization, which is known to be NP hard. A new association algorithm based on GA (genetic algorithm) is presented in this paper to solve the problem. Finally, the simulation results showed that the algorithm improved the detection probability of the multisensor system for its higher correct association percent, and optimized the number of targets to be detected.
基金
国防预研基金资助
关键词
多传感器
多目标
数据关联
遗传算法
多目标检测
multisensor, multitarget, data association, combinatorial optimization, genetic algorithm
