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From Theory to Application: Real-Time Sparse SAR Imaging | IEEE Journals & Magazine | IEEE Xplore

From Theory to Application: Real-Time Sparse SAR Imaging


Abstract:

In recent years, the sparse signal processing technique has shown significant potential in synthetic aperture radar (SAR) imaging, such as image performance improvement a...Show More

Abstract:

In recent years, the sparse signal processing technique has shown significant potential in synthetic aperture radar (SAR) imaging, such as image performance improvement and downsampled data-based image recovery. However, due to the huge computational complexity needed, the existing sparse SAR imaging methods, such as conventional observation matrix-based and azimuth-range decouple-based algorithms, are not able to achieve real-time processing, especially for the large-scale scenes, which seriously restricts its application in some fields, e.g., real-time monitoring and early warning. To solve this problem, this article presents a novel real-time sparse SAR imaging method, which can get a similar image performance to that obtained by the existing sparse imaging methods, to reduce the computational complexity to the same order as that required by matched filtering (MF)-based algorithms. This means that with the proposed method, real-time data processing for practical large-scale scene sparse reconstruction becomes possible. Experimental results based on simulated and real data along with a performance analysis are presented to validate the proposed real-time sparse imaging method.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 58, Issue: 4, April 2020)
Page(s): 2928 - 2936
Date of Publication: 23 December 2019

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