According to the different situation electromagnetic environment, the multiplatform collaborative detection task is planned under the condition of meeting the requirements of multiplatform performance constraints and detection and positioning accuracy. In this article, the 6-tuples of multiple-platform detection attributes is defined, and then a multiple-platform cooperative detection resource scheduling algorithm is established, and a cooperate adaptive evaluation method is proposed for coordination among all the platforms. Calculate the cooperate value among all the platforms. According to the cooperate value, the platform is clustered into a set of the same amount of objects, and then the expected core equipment of each set will be solved. The K-means-clustering technology and Hungarian technology are used to calculate and solve the matrix of the collaborative revenue value of the expected core equipment for the detection target. The feasibility, high adaptability, and the best distribution relationship of the collaborative revenue value are obtained. A kind of resource represented by the expected core equipment is allocated to the corresponding target for work, and the resource scheduling is completed. Multiplatform cooperative electronic detection tasks will be completed effectively in real time, and identify the targets quickly and accurately. Finally, we could complete the countertask.

中文翻译：

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基于K-means聚类算法和匈牙利算法的多平台协同检测资源调度方法

根据电磁环境的不同情况，在满足多平台性能约束和检测定位精度要求的条件下，规划多平台协同检测任务。本文定义了多平台检测属性的6元组，然后建立了多平台协同检测资源调度算法，并提出了一种协同自适应评估方法以实现各平台之间的协调。计算所有平台之间的合作价值。根据合作值，将平台聚类成一组等量的对象，然后求解每组期望的核心设备。采用K-means-clustering技术和匈牙利技术，计算求解检测目标预期核心设备协同收益值矩阵。获得了协同收益价值的可行性、高适应性和最佳分配关系。将期望的核心设备所代表的一种资源分配给相应的工作目标，完成资源调度。多平台协同电子探测任务将实时有效完成，快速准确地识别目标。终于，我们可以完成反任务了。得到协同收益价值的最佳分配关系。将期望的核心设备所代表的一种资源分配给相应的工作目标，完成资源调度。多平台协同电子探测任务将实时有效完成，快速准确地识别目标。终于，我们可以完成反任务了。得到协同收益价值的最佳分配关系。将期望的核心设备所代表的一种资源分配给相应的工作目标，完成资源调度。多平台协同电子探测任务将实时有效完成，快速准确地识别目标。终于，我们可以完成反任务了。