基于博弈理论的认知雷达网络系统设计与管理研究

The netted and cognitive sensor system is an irresistible trend in the field of information,and radar has no exception. Thus, an appropriate theory is needed to investigate how to design and manage cognitive radar networks (CRN) . Game theory is a subject that studies optimization solution in conflict based on mathematics. Applying game theory to CRN is advantageous to explore and utilize the essence of competition. This proposal is unfolded twofold: the noncooperative game between the target and CRN, the cooperative game among the nodes in CRN. Firstly,the game payoff is chosen according to the special exploration mission, such as target detection, parameter estimation and recognition. Secondly, the game models are constituted including the interested parameters, such as the transmitted signal sets, the geometry configuration of radar nodes, energy allocation strategy. Finnally, the strategies of CRN system design and management are obtained via the equilibrium solutions of the (non)coorperative games. We try our best to dig theoretically twofold science issues: which competition mechanisms exist in CRN system, how to utilize the competition mechanisms in CRN for the performance improvement. It will build foundation to improve the detective capability of CRN systems and push forward the progress of the utilization of CRN.

传感器网络化和认知化是信息领域发展的必然趋势，雷达也不例外。如何设计及管理认知雷达网络（CRN）亟需一套合适的理论作为工具对其进行系统地研究。博弈论是一门以数学为基础，研究对抗冲突中最优解问题的学科，将其应用于CRN有利于挖掘CRN中存在的竞争本质并加以利用。本项目拟从非合作目标与CRN间的非合作博弈、CRN各节点间的合作博弈两个方面展开：通过对特定探测任务（目标检测、参数估计、识别）性能的分析得到相应的博弈收益，在此基础上，构建包含感兴趣参数（发射信号集、各雷达节点的几何配置、能量分配等）的博弈数学模型，最后通过对博弈问题均衡的求解，优化得到CRN系统设计和管理的策略。力图从理论上探究"CRN系统中存在哪些竞争机制"和"如何利用CRN中的竞争机制以提高系统性能"两个方面的科学问题，为提高CRN的探测能力提供基础理论、方法和关键技术支撑，推动CRN的实用化进程。

传感器网络化和认知化是信息领域发展的必然趋势，雷达也不例外。如何设计及管理认知雷达网络（CRN）亟需一套合适的理论作为工具对其进行系统地研究。博弈论是一门以数学为基础，研究对抗冲突中最优解问题的学科，将其应用于CRN有利于挖掘CRN中存在的竞争本质并加以利用。本项目从非合作目标与CRN间的非合作博弈、CRN各节点间的合作博弈两个方面展开：通过对特定探测任务（目标检测、参数估计、识别）性能的分析得到相应的博弈收益，在此基础上，构建包含感兴趣参数（发射信号集、各雷达节点的几何配置、能量分配等）的博弈数学模型，最后通过对博弈问题均衡的求解，优化得到CRN系统设计和管理的策略。力图从理论上探究“CRN系统中存在哪些竞争机制”和“如何利用CRN中的竞争机制以提高系统性能”两个方面的科学问题，为提高CRN的探测能力提供基础理论、方法和关键技术支撑，推动CRN的实用化进程。