Abstract：Micro-Doppler features provide an inventive basis for identifying helicopters' rotors. The existing research on the echo model of helicopters' rotors is limited to the micro-Doppler effect caused by the tips of rectangular rotor blades. This study has initially established the full-scatterer echo models of rectangular tip rotor, tapered tip rotor, and parabolic swept tip rotor. Then, utilizing the feature extraction operator, a method of " time-frequency analysis (TFA)-normalized time-frequency processing-frequency 'projection and compression' - 'truncation and amplitude calculation' Fourier transform " was adapted to extract micro-Doppler features. It could effectively translate in the time domain while constantly maintaining the amplitude-frequency characteristics. Finally, an algorithm solving compressed sensing problems in target classification was proposed using the alternating direction method of multipliers (ADMM) and was compared with traditional support vector machines. The effectiveness of the proposed approach was acquired from simulation results.
王冠阳, 李晨, 于英杰, 邓晓波, 芦达, 梁军利, 汪涛. 基于微多普勒特征的直升机目标识别[J]. 空天防御, 2024, 7(2): 63-73.
WANG Guanyang, LI Chen, YU Yingjie, DENG Xiaobo, LU Da, LIANG Junli, WANG Tao. Helicopter Target Recognition Based on Micro-Doppler Feature. Air & Space Defense, 2024, 7(2): 63-73.
