Game Model in Multi-Target Imaging Task Allocation

Xiao-wen Liu, Qun Zhang, Bi‐shuai Liang, Jia Liang, Hui-Wei Zhang
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引用次数: 1

Abstract

For multi-target imaging task, the time to image all of the targets is very limited, and it would be best to use less time to complete each imaging task. Although the radar network which is constituted by multiple independent and distributed radars can increase efficiency and shorten the observation time for multi-target imaging by the division of labor and cooperation, it is necessary for the radar network to design a multi-target imaging task allocation strategy to optimize the observation time of each radar and improve the time resource utilization. However, there is few study focusing on the imaging task allocation problem. Task allocation problem about multi-target inverse synthetic aperture radar (ISAR) imaging in radar network is a distributed decision problem, thus the game theory could be taken into account to solve the task allocation problem. In this paper, the system model about multi-target imaging and the imaging task allocation problem are given firstly. Moreover, a time optimization game model for multi-target imaging task allocation problem is proposed, and the game model is proven to be a potential game model which has at least one pure-strategy Nash equilibrium (NE). Finally, the best-response dynamics is applied to achieve the solution of the imaging task allocation problem, and the convergence of the time optimization is given to verify that the multi-target imaging task allocation problem can be constructed as a potential game model.
多目标成像任务分配中的博弈模型
对于多目标成像任务,对所有目标进行成像的时间是非常有限的,最好使用更少的时间来完成每个成像任务。虽然由多台独立、分布式雷达组成的雷达网络通过分工协作可以提高多目标成像的效率,缩短多目标成像的观测时间,但雷达网络有必要设计一种多目标成像任务分配策略,以优化每台雷达的观测时间,提高时间资源利用率。然而,针对成像任务分配问题的研究很少。雷达网络中多目标逆合成孔径雷达(ISAR)成像任务分配问题是一个分布式决策问题,因此可以利用博弈论来解决任务分配问题。本文首先给出了多目标成像的系统模型和成像任务分配问题。此外,提出了多目标成像任务分配问题的时间优化博弈模型,并证明了该博弈模型是至少存在一个纯策略纳什均衡(NE)的潜在博弈模型。最后,应用最优响应动力学实现了成像任务分配问题的求解,并给出了时间优化的收敛性,验证了多目标成像任务分配问题可以构建为一个潜在的博弈模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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