Immune Algorithm For The Strategy Of One-On-One Helicopter Air Combat

• Main Authors: Wei, Hsintai, 魏鑫泰
• Other Authors: Lan, Jen
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/77888773796254544650

碩士 === 國防大學理工學院 === 兵器系統工程碩士班 === 99 === Modern attack helicopter air combat techniques have developed rapidly. They have become another “air supremacy” Threat. The main objective is air superiority at tree top altitude. The development of helicopter air combat currently integrates high-tech artificial intelligence tactics. This thesis will establish a simulation environment that uses the immune algorithm (IA) to analyze one-on-one helicopter air combat using the machine gun as a melee weapon. This thesis uses the immune algorithm to search for the optimal thrust acceleration, normal acceleration, helicopter roll angle as the air combat strategy command for the next step. We considered the maximum limitations when the attack helicopter is in a combat situation. The particle motion equations are applied to simulate the helicopter movement. This study defines the optimal shooting distance and the shortest escape distance, combined with the bearing angle between the two combating helicopters to form the total objective function in the immune algorithm. This will be used to evaluate the tactical strategy, the basic combat model effect including pursuit, endure, escape and the various helicopter performance values in the immune algorithm. To reduce the random effect, the Taguchi method is applied to find the most robust combination of affinity and concentration in the immune algorithm to improve the search results accuracy. The simulation results show that the immune algorithm performs better than the genetic algorithm (GA). This paper proposes optimal helicopter one-on-one air combat strategy based on the immune algorithm. The feasibility of the proposed method is verified.