Low-altitude Aircraft Interception Decision Based on Self-optimizing Fuzzy Inference

The large-scale application of low-altitude aircraft such as Miniature unmanned aerial vehicles has brought a series of hidden security issues. However, previous research in interception decision technology still has problems such as low level of intelligence in interception decision-making process. A method of interception decision with simple structure and fast calculation is definitely significant. This paper firstly introduces the security issues caused by low-altitude aircraft, then analyzes the shortcomings of current interception decision methods. A low-altitude aircraft interception decision-making method based on self-optimizing fuzzy inference is proposed. The method uses genetic algorithms to optimize the process of fuzzy inference offline through continuous iteration in order to obtain a fuzzy controller that meets the requirements. It can control the entire decision-making process online to guarantee real-time decision. It is demonstrated in hypothetical simulations that it can intercept invading low-altitude aircraft online. As the final result, this method shows the ability to improve the success rate of interception effectively.