Feature Extraction of Precession Targets Based on Feature Extraction of Precession Targets Based on Multi-aspect Micro-Doppler Fusion

Micro-motion feature is one of the crucial features used for ballistic target recognition. Aiming at the model of cone-shaped target, a novel algorithm based on the multi-aspect narrowband radar network is proposed to extract the micro-motion parameters in this paper. Firstly, on the basis of analyzing the micro-Doppler change rule of the equivalent scattering centers on the precession cone-shaped target in detail, the micro-Doppler curve of each scattering center in echo Doppler spectrum is matched and identified by utilizing the correlation of the micro-Doppler among three scattering centers combined with the frequency compensation method. Then based on this, the multi-aspect associated systems of equations are established, and parameters including the precession angle, radius of undersurface and height of the cone-shaped target are extracted jointly. Finally, the simulation results are given for validating the effectiveness and adaptability of the proposed algorithms.