Multiplatform collaborative detection resource scheduling method using K-means clustering algorithm and Hungarian algorithm

摘要

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.