Fast Decision Making Algorithm for Weapon Target Assignment Based on Adaptive Resonance Theory

In order to solve the real-time problem of Weapon Target Assignment(WTA), this paper establishes a mathematical model of WTA based on the division of fire set, and proposes a fast decision making algorithm of Neighborhood Search based on Fuzzy Adaptive Resonance Theory(FART-NS). The fast generalization ability of Fuzzy Adaptive Resonance Theory(FART) is used to improve the real-time performance of the algorithm. The virtual node is introduced to improve the optimization ability of Neighborhood Search(NS) algorithm in WTA solution space. A closed-loop mechanism of fast generalization neighborhood optimization online learning is formed, which makes the FART-NS algorithm robust to training set accuracy and sampling density. Simulation results show that the FART-NS algorithm is better than the mainstream algorithms such as BBA and improved GA in time complexity, and it can balance the real-time performance and convergence of WTA problem.