Computational Methods and Simulation of UAVs’ Micro-Motion Echo Characteristics Using Distributed Radar Detection

The large number of UAVs under supervision at low altitudes have brought serious security risks to the field of air defense. Accurately analyzing the characteristics of UAVs’ echo signals is of great research significance for the detection and recognition of UAVs. Based on the principle of radar detection, the echo spatial correlation in the distributed radar detection mode is studied. According to the influence of different movement speeds on the micro-motion characteristics of UAVs, the echo signal models of UAVs in two flight states are established. Combined with the instantaneous micro-Doppler frequency model of the ideal motion state of UAVs, micro-Doppler frequency calculation functions of UAVs at different attitude angles are constructed. Through simulation calculation, the variation curves between the observation angle and the echo spatial correlation using different detection distances are given. Based on time–frequency images of UAVs in their ideal motion state, changes in the time–frequency images at different motion speeds and attitude angles are analyzed. These research results will help radar detection systems to accurately recognize UAVs in an uncertain motion state and can also provide a basis for predicting the next motion action of UAVs in subsequent target tracking.