多传感器管理中多目标分配的蚁群优化算法

Ant Colony Optimization Algorithm and Its Application in Multi-sensor Multi-target Assignment Problem

在多传感器对多目标的监视环境下,传感器对目标的优化分配是传感器管理的重要研究内容.文章探讨了多传感器多目标优化分配问题,提出了一个基于带目标威胁系数和未获拦截目标数最少的蚁群算法,并对信息素采用最差和最优更新策略.对优化分配算法进行了实验仿真验证.经过实验验证了该分配模型是可行的,能够使传感器资源均匀地分配给目标,更加符合实际应用.

In multi-sensor multi-target surveillance environment,optimizing allocation from sensors to target is an important topic.After discussing the optimizing allocation problem from the multi-sensor to multi-objects,it proposed a ant colony algorithm based on objective threatening coefficient and objective numbers that are not suffering interception are minimum.Then the worst and best pheromone update strategy was used.Simulation experimental results conform that the allocation model is feasible.It can allocate sensor resources to the target equably,and fit the actual application better.