Electromagnetic Vortex Imaging Based on Multiple Measurement Vectors in Low SNR Condition

Abstract

Vortex electromagnetic wave with orbital angular momentum (OAM) has been a great application prospect in the radar imaging field. Due to the use of sparse recovery theory, downsampling makes electromagnetic (EM) vortex imaging suffer from a low signal to noise ratio (SNR). Therefore, the sparse representation model based on multiple measurement vectors (MMV) is proposed, and the maximal measurement number of MMV is derived. Simulation results indicate that the proposed model can increase recovery correct probability, and obtain better imaging results in low SNR condition.