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Journal of Applied Remote Sensing

Multiple-input-multiple-output radar superresolution three-dimensional imaging based on multidimensional smoothed L0
Author(s): Xiaowei Hu; Ningning Tong; Heming Wang; Yuchen Wang
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Paper Abstract

By exploiting the sparsity of radar target image, it is hopeful to obtain a high-resolution target image in multiple-input-multiple-output (MIMO) radar via a sparse representation (SR) method. However, for the three-dimensional (3-D) imaging, the conventional SR method has to convert the 3-D problem into the one-dimensional (1-D) problem. Thus, it will inevitably impose a heavy burden on the storage and computation. A multidimensional smoothed L0 (MD-SL0) algorithm is proposed based on the conventional smoothed L0 algorithm. The proposed MD-SL0 can directly apply to the multidimensional SR problem without transforming to the 1-D case. As a result, a MIMO radar 3-D imaging method via MD-SL0 is achieved with high computation efficiency and low storage burden. Finally, the effectiveness of the method is validated by the results of comparative experiments.

Paper Details

Date Published: 22 August 2016
PDF: 16 pages
J. Appl. Rem. Sens. 10(3) 035017 doi: 10.1117/1.JRS.10.035017
Published in: Journal of Applied Remote Sensing Volume 10, Issue 3
Show Author Affiliations
Xiaowei Hu, Air Force Engineering Univ. (China)
Ningning Tong, Air Force Engineering Univ. (China)
Heming Wang, Air Force Engineering Univ. (China)
Yuchen Wang, Air Force Engineering Univ. (China)

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