Real Time Detection and Identification of UAV Abnormal Trajectory

Abstract

Abnormal behavior detection based on video sequence is a hot field. At the same time, monitoring and tracking the UAV (Unmanned Aerial Vehicle) and identifying its abnormal behavior are great significance for the UAV defense. This paper focuses on the detection and recognition of the UAV abnormal trajectory based on real-time video sequence. By tracking and analyzing the characteristics of the UAV, the detection and recognition of abnormal trajectory are divided into two stages. First, by analyzing the UAV's abnormal trajectory satisfying the change conditions is extracted by the quantitative analysis of the UAV's directional angle change features. Second, the normalized polar path fourier spectrum feature of abnormal trajectory is established, and the feature is combined with window search length to accelerate the classification and identification of the UAV trajectory types. Through the contrast experiment, it shows that the method in this paper has good real-time performance and accuracy for trajectory recognition with scale and translation changes.