Classification of Plates and Trihedral Corner Reflectors Based on Linear Wavefront Phase-Modulated Beam

Wavefront-modulated beams such as vortex beams have attracted much attention in the field of target recognition due to the introduced degrees of freedom. However, traditional wavefront-modulated beams are doughnut shaped, and are not suitable for radar detection or tracking. To solve this problem, a linear wavefront phase-modulated beam with a maximum radiation intensity in the center was proposed in a previous study. In this paper, we continue to study target characteristics under the linear wavefront phase-modulated beam. Through analysis of the target scattering based on the physical optics (PO) method, we find that a part of the monostatic or bistatic radar cross-section (RCS) of the target could be obtained by changing the phase gradient of the modulated beam. Taking this part of RCS for feature extraction, we recognize the plates and trihedral corner reflectors through the support vector machine (SVM) method. For data visualization, we use the t-distributed stochastic neighbor embedding (t-SNE) method for data dimensionality reduction. The results show that the recognition probability of the plates and trihedral corner reflectors can reach 91% with an antenna array having an aperture of 20 wavelengths when the signal-to-noise ratio (SNR) is 20 dB, while the traditional plane beam cannot classify these two targets directly.