Off-the-Grid Sparse Imaging by One-Dimensional Sparse MIMO Array

作者：Li Ding, Shuxian Wu, Xi Ding, Ping Li, Yiming Zhu · 发表于：IEEE Sensors Journal · 年份：2018 · DOI：10.1109/jsen.2018.2873687 · 被引用次数：5 · 研究领域：Microwave Imaging and Scattering Analysis、Antenna Design and Optimization、Millimeter-Wave Propagation and Modeling

Conventional multiple-input multiple-output (MIMO) technique applied into the millimeter-wave and terahertz (THz) imaging applications would suffer from the large number of array elements due to their short wavelengths. In this paper, to reduce the array elements for azimuth-range imaging, a 1-D sparse MIMO array is introduced that combines with the wideband emitted signal to achieve 2-D imaging in the near field. Provided with these greatly reduced spatial samples measured by the sparse array, an off-the-grid sparse imaging algorithm is proposed to recover the arbitrarily distributed scatterers in a 2-D plane. In particular, the proposed approach takes advantages of the MIMO geometry and matrix pencil (MP) method. It utilizes the echo in wave-number domain which is featured by the MIMO geometry to make a lossless dimension reduction from the 2-D unknown position of each scatterer into a local 1-D frequency. After estimating those local 1-D frequencies by the MP method, an MIMO-structure-determined filter is developed to fulfill the inverse mapping and finally achieve imaging without the pairing problem. Simulations and experiments verify the effectiveness of the proposed approach.