摘要
为解决区域搜索和目标跟踪2种任务协同时对传感器资源的竞争问题,提出了一种多传感器调度方法。针对双任务协同背景,将传感器调度转换为多目标优化问题,以搜索性能和跟踪性能为优化目标建立了目标函数;建立了区域搜索模型,考虑目标的新生、消亡和转移,将未被发现目标的更新过程建立为非齐次泊松过程,提出以漏警损失量化区域搜索性能;建立了目标跟踪模型,引入后验克拉美罗下界(PCRLB)量化未来时刻的跟踪性能;针对最优调度方案求解,在传统多目标差分进化算法的基础上,引入混沌映射理论和双种群协同方法,提出了混沌映射-多目标协同差分进化算法(CM-MOCDEA)以提高寻优能力。仿真实验验证了所提优化算法能够兼顾收敛性和多样性,具有较强的全局搜索能力;所提方法能够有效分配传感器资源完成区域搜索和目标跟踪任务,从而获得较高的作战收益。
A multi-sensor scheduling method is proposed to address the competition of sensor resources during simultaneous execution of area search tasks and target tracking tasks.Firstly,for the dual-task cooperation,sensor scheduling is transformed into a multi-objective optimization problem,and the search performance and tracking performance are taken as the optimization objectives.Secondly,the area search model is established,in which the process of updated undetected targets is built as a non-homogeneous Poisson process,considering the rebirth,extinction,and transfer of targets.The missed alarm loss is proposed to quantify the search performance.Then,the target tracking model is established,and the posterior Carmér-Rao lower bound(PCRLB)is introduced to quantify the tracking performance in the future.Finally,to search the best scheduling scheme,a chaotic map multi-objective cooperative differential evolution algorithm(CM-MOCDEA)is proposed,utilizing the chaotic mapping theory and dual population cooperative method based on the traditional multi-objective differential evolution algorithm.Simulation results show that the proposed algorithm can consider both convergence and diversity,and has a strong global search ability.The proposed scheduling method can also effectively allocate sensor resources to complete area search and target tracking tasks,thus achieving higher operational gains.
作者
张昀普
付强
单甘霖
黄燕
ZHANG Yunpu;FU Qiang;SHAN Ganlin;HUANG Yan(Shijiazhuang Campus,Army Engineering University,Shijiazhuang 050003,China;The 32316 Unit of the Chinese People’s Liberation Army,Urumqi 830001,China)
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2024年第3期850-860,共11页
Journal of Beijing University of Aeronautics and Astronautics
关键词
传感器调度
区域搜索
目标跟踪
多目标优化
多目标差分进化算法
sensor scheduling
area search
target tracking
multi-objective optimization
multi-objective differential evolution algorithm
