Unmanned aerial vehicle attack and defense decision-making method based on self-adaptive step discrete wolf pack algorithm

Abstract

The invention discloses an unmanned aerial vehicle attack and defense decision-making method based on a self-adaptive step discrete wolf pack algorithm. The unmanned aerial vehicle attack and defensedecision-making method comprises the steps of S1, obtaining an air combat situation, combat performance and a target intention, and building a comprehensive threat function; S2, determining an artificial wolf code length L according to the missile number m owned by an unmanned aerial vehicle and the enemy unmanned aerial vehicle number n, and establishing an unmanned aerial vehicle attack and defense distribution model according to constraint conditions; S3, designing the self-adaptive step discrete wolf pack algorithm, executing the self-adaptive step discrete wolf pack algorithm by taking the comprehensive threat function as a fitness index calculation formula of the self-adaptive step discrete wolf pack algorithm, and solving a corresponding optimal solution; and S4, performing unmannedaerial vehicle attack and defense decision making according to the corresponding optimal solution. According to the unmanned aerial vehicle attack and defense decision-making method based on the self-adaptive step discrete wolf pack algorithm, the intelligent behavior of the discrete wolf pack algorithm is described by defining the crossover operator and the motion operator, and the convergence speed of the discrete wolf pack algorithm is increased by adopting a self-adaptive running step length mode, so that the problem that the attack and defense decision-making speed of the unmanned aerialvehicle is difficult to meet the real-time air combat requirement when the problem scale is too large is solved.

Description

technical field [0001] The invention relates to the technical field of intelligent decision-making for unmanned aerial vehicles, in particular to an attack and defense decision-making method for unmanned aerial vehicles based on an adaptive step size discrete wolf pack algorithm. Background technique [0002] Offensive and defensive decision-making refers to the process in which fighter planes assign our UAV missiles to enemy UAVs during air combat, and then damage the enemy UAVs, thereby ensuring our air combat situational advantage and even winning the air combat. In recent years, with the rapid development of drone technology, drones in the air battlefield have gradually become a reality. [0003] With the development of various high and new technologies, different drones and missile weapons have been put into the air battlefield, and the scale of air combat has gradually increased. At the same time, compared with manned aircraft, UAVs lack the real-time guidance of pilo...

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Problems solved by technology

In addition, it also has certain advantages over other algorithms in solving discrete problems such as knapsack problem and traveling salesman. It has better breadth development and deep mining capabilities, and can better solve discrete combinatorial o

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