MIMO coded generalized reduced dimension fourier algorithm for 3D microwave imaging

Amir Masoud Molaei, Shaoqing Hu, Rupesh Kumar, Okan Yurduseven

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In this paper, to accelerate data acquisition and image reconstruction procedures in a multistatic short-range microwave imaging scenario, an orthogonal coding approach with Fourier domain processing is presented. First, a special two-dimensional (2D) multiple-input multiple-output (MIMO) structure is introduced to fully electronically synthesize the 2D aperture. Then, the model of the transmitted and received signals by a MIMO stepped-frequency-modulated radar is presented, with special considerations about orthogonal, balanced and optimal sequences. On the receiver side, the backscatter frequency response extraction process is formulated with the aim of obtaining individual information of all channels. Finally, based on the introduced model, a fast Fourier-based algorithm with reduced dimensions, named MIMO coded generalized reduced dimension Fourier (CGRDF), is mathematically derived. It includes extracting phase and amplitude compensators with the aim of mapping 4D to 2D spatial data, transferring the backscatter transfer function from the spatial domain to the wavenumber domain, extracting the smoothing filter, compensating the curvature of the wavefront of all scatterers, extracting the reflectivity function and an additional range compensator. The results of numerical simulations show the satisfactory and reliable performance of the proposed approach in terms of the information retrieval process and processing speed.
Original languageEnglish
JournalIEEE Transactions on Geoscience and Remote Sensing
Early online date22 Mar 2023
Publication statusEarly online date - 22 Mar 2023


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