Unmanned combat aerial vehicle maneuvering gaming method with intuition fuzzy information

Abstract

The invention discloses an unmanned combat aerial vehicle maneuvering gaming method with intuition fuzzy information. The method comprises steps of firstly, establishing a strategy set of an unmannedcombat aerial vehicle maneuvering decision; then, carrying out multi-attribute intuition fuzzy estimation on selectable maneuvering strategies according to the threatening size so as to obtain an intuition fuzzy payment matrix of unmanned combat aerial vehicle maneuvering gaming; establishing a unmanned combat aerial vehicle maneuvering gaming planning mode with intuition fuzzy information under an undetermined environment; and finally, using an improved differential evolution algorithm, solving the mode so as to obtain the optimal maneuvering gaming strategy of the unmanned aerial vehicle under the undetermined environment. According to the invention, the optimal decision problem of the unmanned combat aerial vehicle maneuvering under the undetermined environment is mainly solved.

Description

technical field [0001] The invention belongs to the field of autonomous decision-making in unmanned aerial combat, in particular to a maneuvering game method for unmanned aerial combat with intuitive fuzzy information. Background technique [0002] In the process of air combat, unmanned combat aircraft need to make optimal tactical plans or maneuvers based on complex battlefield situation information. The quality of UAV decision-making mechanism is the key to the successful completion of air combat missions. At present, there have been a lot of achievements in the autonomous decision-making of UAVs at home and abroad. The methods commonly used for maneuver decision-making problems include influence graphs, neural networks, genetic algorithms, Bayesian networks, and game theory. Among them, the game theory method can predict and analyze the air combat situation more objectively because it fully considers the mutual relationship between the opposing sides. The application of g...

AI Technical Summary

Problems solved by technology

At present, the research on air combat decision-making problems based on game theory is mainly carried out in a certain environment, but in the actual environment, due to the influence of factors such as airborne sensor errors and enemy interference signals, the situation information obtained by UAVs often has ambiguity, so it is more practical to study the air combat decision-making of UAVs in uncertain environments

[0003] In addition, the use of intelligent algorithms to solve Nash equilibrium can solve the shortcomings of traditional methods that are complex in calculation and only applicable to a single problem. Currently, the solutions to Nash equilibrium mainly include genetic algorithm (GA), particle swarm optimization (PSO) algorithm, simulated annealing (SAA), etc. Intelligent algorithms, these different intelligent algorithms have their own advantages, but the current research results cannot fully take into account the global search ability and evolution speed of the algorithm

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