通信学报2011，Vol.32Issue(6)：17-23,7.
基于蚁群-遗传算法的改进多目标数据关联方法
Improved AC-GA based data association method for multi-target tracking
摘要
Abstract
An AC-GADA (ant colony-genetic algorithm data association) algorithm was proposed to deal with the data association problem for multi-target tracking. This algorithm designed difference pheromone for each ant and improved global pheromone increment model, and combined crossover and mutation strategy with fitness of population model in order to improve rate of convergence and avoid the appearance of local extremum. The comparison with ACDA (ant colony data association) and JPAD (joint pobabilistic data association) proved its efficiency and superiority.关键词
数据关联/多目标/蚁群算法/遗传算法Key words
data association/ multi-target/ AC/ GA分类
信息技术与安全科学引用本文复制引用
袁东辉,刘大有,申世群..基于蚁群-遗传算法的改进多目标数据关联方法[J].通信学报,2011,32(6):17-23,7.基金项目
国家自然科学基金资助项目(60773099,60873149,60973088) （60773099,60873149,60973088）
国家高技术研究发展计划("863"计划)基金资助项目(2006AA10Z245,2006AA10A309) （"863"计划）
中央高校基本科研业务费专项基金资助项目(200903189,200903182) （200903189,200903182）
