Three-dimensional near-field microwave imaging approach based on compressed sensing

Considering the difficulties in large-scale data processing and low imaging resolution of traditional near-field microwave imaging approach, a new near-field imaging approach based on compressed sensing is proposed in this paper. Under the premise of discretization of imaging scene, the near-field imaging model based on compressed sensing is built firstly. Then the random sparse observation is adopted in the proposed approach to reduce the sampling data volume and improve imaging efficiency, and the optimization reconstruction algorithm is used to obtain an improved higher resolution target image. The effectiveness of this approach is verified through simulation experiment and the microwave anechoic chamber real test experiment. The results show that, compared with the traditional imaging result, the proposed approach in this paper is of higher resolution, even if with a small amount of echo data.