Multiple-input-multiple-output synthetic aperture radar (MIMO-SAR) is being studied and used in more and more sensing applications. However, to deal with large-size scanning data without acceleration technology, there is still a certain distance away from real-time operation using the previous state-of-the-art imaging algorithms, which must use complicated interpolation or iteration operations. To conquer this difficulty, a fast imaging algorithm is developed for 3-D near-range imaging on MIMO-SAR. An appropriate expansion is carried out to the coupling phase term, and thus the differential correction for the MIMO data set can be realized with only a range inverse fast Fourier transform (IFFT) and a matched filtering, which are easy to implement. The computational complexity of the algorithm is O(N4log2N ), which is lower than the previous state-of-the-art algorithms. Short-range measurements on a millimeter-waveband MIMO-SAR with different distributed targets demonstrate the performance of the proposed algorithm. Real-time operation is achieved using the algorithm even with a regular CPU.
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Kai Tan (2020) studied this question.