CASIA OpenIR  > 学术期刊  > 自动化学报
面向飞行目标的多传感器协同探测资源调度方法
汪梦倩; 梁皓星; 郭茂耘; 陈小龙; 武艺
Source Publication自动化学报
ISSN0254-4156
2023
Volume49Issue:6Pages:1242-1255
Abstract针对飞行目标机动性带来的多传感器协同探测资源调度动态性需求,提出一种新的基于近端策略优化(Proximal policy optimization, PPO)与全连接神经网络结合的多传感器协同探测资源调度算法.首先,分析影响多传感器协同探测资源调度的复杂约束条件,形成评价多传感器协同探测资源调度过程指标;然后,引入马尔科夫决策过程(Markov decision process, MDP)模拟多传感器协同探测资源调度过程,并为提高算法稳定性,将Adam算法与学习率衰减算法结合,控制学习率调整步长;最后,基于改进近端策略优化与全卷积神经网络结合算法求解动态资源调度策略,并通过对比实验表明该算法的优越性.
Keyword多传感器协同 资源调度 马尔科夫决策过程 强化学习
DOI10.16383/j.aas.c210498
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/56135
Collection学术期刊_自动化学报
Recommended Citation
GB/T 7714
汪梦倩,梁皓星,郭茂耘,等. 面向飞行目标的多传感器协同探测资源调度方法[J]. 自动化学报,2023,49(6):1242-1255.
APA 汪梦倩,梁皓星,郭茂耘,陈小龙,&武艺.(2023).面向飞行目标的多传感器协同探测资源调度方法.自动化学报,49(6),1242-1255.
MLA 汪梦倩,et al."面向飞行目标的多传感器协同探测资源调度方法".自动化学报 49.6(2023):1242-1255.
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