Design of Target Detection Algorithm in Airport Flight Area Based on Fuzzy Clustering

When the airport is in normal operation all day, the airport flight area bears the important responsibility of taking off and landing. Runway intrusion will disturb the operation order of the airport, but it will seriously affect the safety of all passengers and crew, and the runway safety will be severely tested. In this study, a target detection algorithm in airport flight area based on fuzzy clustering is proposed, and KF (Kalman filtering) is used to predict the area where the moving target may be located at the next moment, so as to narrow the search target area and achieve the goal of fast tracking the moving target. On the basis of FCM (fuzzy c-means) method, the idea of fuzzy clustering is used to suppress noise. According to different membership degrees, the points far from the center of the set can be suppressed. The results show that the correlation filter algorithm combined with scale filter can estimate the scale of moving objects, and the algorithm in this paper is robust when tracking moving objects with varying scales. Tracking multiple moving targets independently at the same time, because KF estimation can get the continuous moving state of moving targets, on the basis of ensuring the detection accuracy, the running speed of the target detection algorithm in this paper has been greatly improved.