基于自适应遗传算法的多传感器多目标静态数据关联

Multisensor Multitarget Static Data Association Based on Adaptive Genetic Algorithm

利用多传感器跟踪多目标技术中最重要的问题是目标关联问题 ,而常见的关联算法要么计算量大 ,要么实际运用中效果不理想。本文提出了利用自适应遗传算法来解决在传感器存在漏检、检测空域中目标个数未知情况下 ,单平台多传感器数据融合系统对目标进行检测时的静态数据关联问题。实验结果表明 ,这种算法具有很高的关联成功率 。

One of the most important problems that must be resolved in multi-target tracking with multi-sensor is the data association.But the conventional association algorithm have either heavy computing burden of the result is not ideal.In this paper,we use adaptive genetic algorithm to deal with the static problem of associating measurements from multi-sensors in a single platform with missed detection and uncertain number of objects.At last,the experiment results illustrate higher correct association percent and improve detecting probability of multi-sensor data-fusion system.