High resolution 3D imaging in MIMO radar with sparse array

High resolution three-dimensional (3D) imaging method using MIMO radar with sparse array is studied in this paper. A method based on compressive sensing (CS) is firstly given. However, the CS-based method has the off-grid problem which will reduce the estimation accuracy of scatterers' position on the target. Moreover, a high dimensional measurement matrix is required in the CS-based method, which will lead to a heavy storage and computation burden. To solve the two problems of CS, a new method based on matrix completion is proposed in this paper. After reshaping the sparse 3D echo into a low-rank structured matrix, the full 3D echo can be recovered by solving a nuclear norm minimization problem. Then the accurate position of scatterers can be estimated by applying multi-dimensional harmonic retrieval methods to the full 3D echo. Finally, the high resolution 3D image of targets is reconstructed. The effectiveness of the method is validated by the results of comparative simulations.