Research On The Algorithmic Optimtzation Of Aircraft Collision Avoidance System

With the rapid development of the air transport industry, more and more aircraft have appeared on busy routes. Unmanned aerial vehicles and other new aircraft have been given the license into sky under the advance of computer and electronics technology. So we can foresee that manned aircraft and unmanned aircraft appear together on the route will become normal. Although TCAS system can make sure flight safety of aircraft at this stage, there are many uncertain factors when TCAS of this stage protect the safety of aircraft flying in the future because of its own flaws. This makes us optimize and upgrade aircraft collision avoidance system.This paper studies how to optimize algorithms of aircraft collision avoidance system.It uses more mature algorithms at this stage, such as Artificial Potential Field algorithm(APF), Ant Colony Algorithm(ACA) and Particle Swarm Optimization algorithm(PSO).It optimizes and combines these algorithms, then choose the best algorithm--Ant Colony-Artificial Potential Field algorithm form them in compliance with design of aircraft collision avoidance system. We simulate and verify the best algorithm finally.