Pseudo-Trapezoidal Fast Factorized Backprojection Algorithm for Near-Field Sparse MIMO Array 3-D Imaging

In the near-field condition, the wavenumber spectrum exhibits spatial variance, which renders the fast factorized backprojection algorithm (FFBPA) ineffective in improving the imaging efficiency. In this article, an image-domain compensation function is introduced to eliminate the spatial variance of the wavenumber spectrum, thereby achieving wavenumber spectrum compression and relaxing sampling requirements. After compensation, the wavenumber spectrum bandwidth is only related to the range, so a pseudo-trapezoidal coordinate is adopted to avoid the sampling redundancy. At the same time, since the unambiguous sampling interval varies nonlinearly with the aperture length, a nonlinear aperture partitioning strategy is proposed to reduce the computational complexity and facilitate the use of non-interpolation methods to achieve resolution enhancement. By adopting the above techniques, the method can achieve a lower computational load than the frequency domain imaging algorithms. Experiments conducted on a variety of multiple-input multiple-output (MIMO) array topologies verify the effectiveness of the proposed method. The results demonstrate that the method can be applicable to any MIMO array topology and can greatly improve the imaging efficiency while accurately reconstructing the target.