Dimension-Factorized Range Migration Algorithm for Regularly Distributed Array Imaging

Abstract

The two-dimensional planar MIMO array is a popular approach for millimeter wave imaging applications. As a promising practical alternative, sparse MIMO arrays have been devised to reduce the number of antenna elements and transmitting/receiving channels with predictable and acceptable loss in image quality. In this paper, a high precision three-dimensional imaging algorithm is proposed for MIMO arrays of the regularly distributed type, especially the sparse varieties. Termed the Dimension-Factorized Range Migration Algorithm, the new imaging approach factorizes the conventional MIMO Range Migration Algorithm into multiple operations across the sparse dimensions. The thinner the sparse dimensions of the array, the more efficient the new algorithm will be. Advantages of the proposed approach are demonstrated by comparison with the conventional MIMO Range Migration Algorithm and its non-uniform fast Fourier transform based variant in terms of all the important characteristics of the approaches, especially the anti-noise capability. The computation cost is analyzed as well to evaluate the efficiency quantitatively.

A Transverse Spectrum Deconvolution Technique for MIMO Short-Range Fourier Imaging

“…However, this last step is crucial and represents the most time-consuming process in this algorithm, especially for large arrays of unequal sizes where prior zero padding and spatial interpolation are required to work with suitable plane wave grids. Sparse arrays have been implemented in the MIMO systems to mitigate this computational limitation, exploiting the complementary spatial diversities of the transmit and receive arrays to ensure a full k-space coverage [19], [20] enabling the development of appropriate rapid processing techniques in this paper [21]. Furthermore, the recent development of compressive systems allowing for the multiplexing of a very large number of transmitted and received waveforms [14], [22] helped overcoming the hardware limitations inherent to high-resolution systems, leading to a growing need of efficient MIMO algorithms compatible with large and densely populated antenna arrays.…”