Micro-Doppler-assisted Unmanned Aerial Vehicle Formation Detection Method in Urban Environments
Considering the phenomena of complex electromagnetic environment,multipath clutter and dense interference signals in complex urban environments,the traditional Unmanned Aerial Vehicle(UAV)detection method extracts the target Doppler information for detection by obtaining echo signals,which is susceptible to environmental impacts and leads to unsatisfactory detection results.A micro-Doppler-assisted formation detection method for UAVs in urban environments is proposed in this paper,which makes full use of micro-motion characteristics to improve detection accuracy.Firstly,parametric modeling characterizes the radar echo micro-Doppler signals of UAV rotor blades in urban complex environments,and detects the micro-Doppler scintillation pulses by using YOLOv5s to effectively extract the positional information.Then,the Pulse Repetition Interval(PRI)transform of the radar signal sorting method is introduced to classify and obtain the number of UAV formations.Finally,K-means algorithm is utilized to verify the accuracy of the UAV formation detection method.The results show that the proposed method has a detection accuracy of more than 90％for seven UAVs at a signal-to-noise ratio of 2 dB,and can be used for UAV formation detection in urban complex environments where there are interfering pulses,multipath effects,and local pulse loss.
万方数据
维普
