Geometrically-Inspired Sparse MIMO Array Design for Enhanced mm-Wave Near-Field Imaging

In this paper, an efficient method of sparse MIMO array design is proposed to enhance the millimeter-wave near-field imaging by utilizing the geometric properties of the virtual array with uniform coverage of two-dimensional aperture and the minimal element shadowing. Starting with the optimization of sparse single-input multiple-output (SIMO) array, the sparse MIMO array is reconstructed in a reverse way by a genetic algorithm with nested inner and outer loops. In both the loops of optimization, the advantage of spiral function is exploited to optimize the SIMO and the receiving sub-array of MIMO array. The desired attributes of geometric properties required for virtual array therefore can be seamlessly transferred to the sparse MIMO array with the assistance of the temporary SIMO array. Experiments are conducted to compare the imaging performance of the proposed array with some conventional sparse MIMO arrays. Both the results of the point-spread-function analysis and the millimeter-wave near-field imaging demonstrate that under the same number of array elements, the sparse MIMO array obtained by our proposed method exhibits superior imaging performance over other comparison arrays, delivering the reduced grating and side lobes levels.