Decoupled Parameter Estimation of Small AAV Rotors Using FMCW Radar

The parameter estimation of the rotors of unmanned aerial vehicles (UAVs) based on inverse synthetic aperture radar (ISAR) has great help to the detection and recognition of the UAVs. When facing undersampling in azimuth, most of the existing algorithms have the problem of limited parameter estimation accuracy and high algorithm complexity, and the performance of these algorithms often greatly decreases. In this study, a novel and efficient parameter estimation method of the UAV rotors is proposed. The method firstly realizes the parameter decoupling, which simplifies the complex multi-parameter searching problem into three one-dimensional parameter estimation problems. More importantly, the proposed strategy has robust performance under low PRF conditions, which surpasses the existing ISAR based methods. The scattering point distribution of the rotor blade is recovered with the orthogonal matching pursuit (OMP) method, leading to an accurate estimate of the blade length when facing low PRFs. Experiments on simulated and measured data have shown that the proposed method is effective under different undersampling, SNR and phase noise cases. The rotor parameters are estimated with sufficient accuracy and the running time is only about 10% of the conventional traversal algorithms.