基于灰色层次分析法的有人/无人协同作战效能评估

Effectiveness Evaluation of Manned-Unmanned Collaborative Combat Based on Grey Analytic Hierarchy Process

当前和今后相当长一段时期内,战场的机械化、信息化、智能化将长期并存、并行发展。有人/无人协同作战可以通过各无人系统与有人系统之间的资源调度、态势统一、任务整合来进一步提高作战系统的作战效能。基于灰色层次分析法,结合径向基函数(Radial Basis Function,RBF)神经网络进行数据整理,对有人/无人协同作战效能进行科学评估,提出了一种新的评估模型,为优化协同作战体系结构和提高协同作战能力提供了理论依据。围绕有人/无人协同作战的作战任务和能力需求构建了相关评估指标体系,基于灰色层次分析法与RBF神经网络设计了有人/无人协同作战评估模型,并进行了仿真实验分析。仿真结果表明,该方法能够实现对有人/无人协同作战效能客观有效的评估。

In the current and foreseeable future,mechanization,informatization,and intelligence will coexist and develop simultaneously on the battlefield.The coordination of manned and unmanned systems can further enhance the operational effectiveness of the combat system through resource allocation,situational awareness,and task integration between different unmanned and manned systems.The authors aim to scientifically evaluate the effectiveness of manned-unmanned coordination in combat by applying the Gray Analytic Hierarchical Process(GAHP)method and combining it with the Radial Basis Function(RBF)neural network for data analysis.A new evaluation model is explored to provide theoretical basis for optimizing the structure and improving the capabilities of the coordinated combat system.By focusing on the combat tasks and capability requirements of manned-unmanned coordination,a relevant evaluation index system is established,and a manned-unmanned coordination assessment model is designed based on the GAHP and RBF neural network.Simulation experiments have been conducted to analyze the effectiveness.The results demonstrate that this method can evaluate the effectiveness of manned-unmanned coordination in combat objectively and effectively.