Near-Field Synthetic Spectrum Imaging Algorithm Based on Single-Frequency Sparse MIMO Array

Abstract

This letter presents a two-dimensional near-field synthetic spectrum imaging algorithm based on a single-frequency sparse multiple-input–multiple-output (MIMO) array. By using an especially defined backward spreading function, the proposed algorithm migrates the scattered wave field under different illuminations. A synthetic spectrum can be obtained by synthesizing the spectrums of these migration results and then interpreted to the final reconstruction. The migration processing enables the algorithm to adapt to arbitrary apertures. Meanwhile, the influences of the limited aperture, the spreading loss, and the wavefront curvature in the near field are considered and compensated. High processing speed is achieved by using a large interpixel spacing during the migration processing and by the fast Fourier transform in the frequency-wavenumber (f-w) domain. Simulations and experiments are carried out, and the results demonstrate both the high-computational efficiency and the high flexibility for arbitrary sparse MIMO array apertures.