An unmanned air combat system based on swarm intelligence

Abstract

Unmanned aerial vehicles (UAVs) are usually controlled by radio or by autonomous control algorithms. Compared with manned aerial vehicles, they have great advantages in performing dangerous tasks but, presently, no UAV system can cope with high-intensity air combat. In addition, the robustness of a single UAV cannot be guaranteed in air combat missions; on the other hand, a multi-UAV system not only ensures this robustness but also improves the mission success rate by using saturation attacks. Therefore, this paper presents a multi-UAV air combat system based on swarm intelligence. Considering the problem of multi-UAV cooperative arrival at the air battlefield and the accomplishment of combat tasks, the aerodynamic model of the aircrafts and the threat area on the path to the battlefield are modeled; the path planning is completed through an ant colony algorithm. Based on the control algorithm of single-UAV finite-state machine and the cooperation of multiple UAVs, an autonomous control algorithm for multi-UAV systems is proposed to improve the success rate of UAV clusters in air combat. The effectiveness of the proposed algorithm is tested with a simulation platform.