Extraction of Micro-Doppler Features from Unmanned Aerial Vehicles Based on Electromagnetic Simulation

Abstract

With the rapid development of drone technology, the micro-Doppler signature plays a crucial role in the recognition and classification of drones. However, existing methods for extracting micro-Doppler signals are often affected by the complex structure of targets and environmental interferences, leading to issues of low extraction accuracy and efficiency. In response to this challenge, this paper investigates a method for extracting rotor micro-Doppler signals of Unmanned Aerial Vehicles (UAVs) based on electromagnetic simulation. By establishing the geometric model of the target object and using the physical optics method for RCS measurement of the model, the obtained data is utilized for inverse ISAR imaging to obtain the scattering center positions and scattering intensity of each point on the rotor. A model for extracting micro-Doppler properties is established, enabling accurate and efficient extraction of micro-Doppler characteristics for target objects. The proposed method can be widely applied to extract and study the micro-Doppler characteristics of different types of drones.