Task demand-based heterogeneous unmanned aerial vehicle cluster collaborative optimal configuration method

Abstract

The invention provides a task demand-based heterogeneous unmanned aerial vehicle cluster collaborative optimal configuration method. The method comprises: firstly, respectively constructing a battlefield required firepower attack efficiency index system and an attack unmanned aerial vehicle firepower attack efficiency index system, and respectively performing efficiency evaluation on the systems by adopting an analytic hierarchy process to obtain battlefield required firepower attack efficiency and heterogeneous unmanned aerial vehicle cluster firepower attack efficiency; then, comparing and evaluating the cruising ability of the heterogeneous unmanned aerial vehicle cluster and the cruising ability required by the battlefield; and finally, constructing an integer programming configurationmodel with constraints by utilizing the evaluation result, and solving by adopting a Monte Carlo method to obtain an optimal configuration result of the heterogeneous unmanned aerial vehicle cluster.By adopting the method, the heterogeneous unmanned aerial vehicle cluster is optimally configured before the task is executed, so that the risk of task failure of the unmanned aerial vehicle clusterand the combat cost can be reduced.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicle cluster cooperative operations, and in particular relates to an optimal configuration method for heterogeneous unmanned aerial vehicle cluster coordination based on mission requirements. Background technique [0002] In the context of modern information warfare, UAVs are developing in the direction of miniaturization and miniaturization. In order to cope with the complex battlefield environment, the use of cluster combat can greatly improve the combat effectiveness of drone clusters. UAV swarm operations require reasonable configuration of different types and functions of UAVs in the swarm. The swarm obtained from a reasonable configuration can give full play to the combat capabilities of each UAV, reducing the risk of mission failure and combat costs. [0003] The essence of UAV swarm configuration is to comprehensively evaluate the effectiveness of the enemy battlefield and our...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies of the prior art, the present invention provides a collaborative optimal configuration method for heterogeneous UAV clusters based on task requirements, which is used to solve the problem of configuring the structure and scale of heterogeneous UAV clusters before task execution

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