基于神经网络虚拟自我对局的雷达干扰博弈策略设计方法

• Format: Patent
• Language: Chinese
• Published: 02.08.2024
• Subjects: ANALOGOUS ARRANGEMENTS USING OTHER WAVES; CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES; MEASURING; PHYSICS; RADIO DIRECTION-FINDING; RADIO NAVIGATION; TESTING

本发明公开了一种基于神经网络虚拟自我对局的雷达干扰博弈策略设计方法，包括：构建雷达和干扰机对应的扩展式多回合博弈交互模型；其中，所述雷达和干扰机分别设置为神经网络虚拟自我对局中的主体：基于所述扩展式多回合博弈交互模型，获取雷达和干扰机之间的交互信息，并对所述交互信息进行编码，所述交互信息中包括博弈状态转移信息和最优反应行为信息；基于神经网络虚拟自我对局对编码后的交互信息进行求解，以获取雷达和干扰机之间的多个博弈策略组合；获取每个博弈策略组合的平均利用度，并将平均利用度最小值对应的博弈策略组合确定为目标博弈策略组合。本发明能够高效、准确地获取雷达和干扰机之间的博弈情况。 The invention discloses a radar interference game strategy design method based on neural network virtual self-game. The method comprises the following steps: constructing an extended multi-round game interaction model corresponding to a radar and a jammer; wherein the radar and the jammer are respectively set as subjects in neural network virtual self-match: based on the extended multi-round game interaction model, interaction information between the radar and the jammer is acquired, the interaction information is encoded, and the interaction information comprises game state transition information and optimal reaction behavior information; solving the encoded interaction information based on a neural network virtual self-match