Feature Extraction of Space Cone-shaped Target Based on Narrow-band Radar Networks

The micro-Doppler modulation caused by precession is considered as an important signature for the discrimination of space cone-shaped target. A novel feature extraction method for precessing cone-shaped target with narrow-band radar networks is proposed in this paper. Based on analysis of the scattering properties of the cone-shaped target, this paper first derives the scattering centers theoretical Instantaneous Frequency (IF) variations induced by precession, and the IF variations obtained from multiple radar aspects are matched according to their spectrum entropy. Then according to the properties of IF variations of the top and bottom scattering centers under different radar aspects, the precession and geometry feature extraction method is proposed for estimating the targets parameters, such as height, bottom radius, location of barycentric, precession angle etc. Experiments based on the electromagnetic computation data verify the validness and accuracy of the proposed method.