Unmanned aerial vehicle cluster combat game decision method based on quantum krill population evolution mechanism

Abstract

The invention relates to an unmanned aerial vehicle cluster combat game decision method based on a quantum krill population evolution mechanism, which comprises the following steps: establishing an unmanned aerial vehicle cooperative combat game decision model; initializing the quantum krill group; calculating the fitness value of each quantum krill position in the quantum krill group according toa fitness function; updating a quantum rotation angle and a quantum position of each quantum krill; carrying out fitness calculation on the updated position of each quantum krill in the quantum krillgroup, obtaining the updated position of each quantum krill through a mapping rule, and calculating the fitness of the position; determining the global optimal quantum position of the quantum krill population; circularly judging; outputting the global optimal position of the quantum krill group and mapping the global optimal position into a mixed strategy combination of games. According to the method, the unmanned aerial vehicle cluster combat command decision is analyzed in combination with the game theory, so that both sides of the operation can obtain the maximum benefit through the rational decision analysis, the battlefield environment of the unmanned aerial vehicle cluster operation is better met, and the applicability is stronger.

Description

technical field [0001] The invention relates to a game decision-making method for UAV swarm combat, in particular to a game decision-making method for UAV swarm combat based on the evolution mechanism of quantum krill swarms, which combines game theory to conduct decision-making analysis of UAV combat command, which belongs to the field of The field of human-machine autonomous control. Background technique [0002] UAV swarm combat is a process in which multiple UAVs with partial autonomy perform combat tasks together. It is the main combat form of future air combat. Reasonable UAV task assignment is an important means to improve combat efficiency. Facing the complex battlefield environment, the task allocation of drones has become the primary consideration for decision-makers. [0003] Game theory is mainly to study the rational behavior of interdependence between agents, and to maximize the benefits or minimize the punishment through rational decision-making. This is very...

AI Technical Summary

Problems solved by technology

However, it mainly focuses on the research on UAV flight control technology, and less research on tactical command

[0005] Although the above methods can obtain corresponding results in solving the UAV combat decision-making problem, they do not fully consider the conflicting decision-making behavior of both combatants.

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