Multiple-input-multiple-output radar superresolution three-dimensional imaging based on multidimensional smoothed L0

Xiaowei Hu; Ningning Tong; Heming Wang; Yuchen Wang

doi:10.1117/1.JRS.10.035017

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22 August 2016 Multiple-input-multiple-output radar superresolution three-dimensional imaging based on multidimensional smoothed L0

Xiaowei Hu, Ningning Tong, Heming Wang, Yuchen Wang

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J. of Applied Remote Sensing, 10(3), 035017 (2016). https://doi.org/10.1117/1.JRS.10.035017

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.

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Xiaowei Hu, Ningning Tong, Heming Wang, and Yuchen Wang "Multiple-input-multiple-output radar superresolution three-dimensional imaging based on multidimensional smoothed L0," Journal of Applied Remote Sensing 10(3), 035017 (22 August 2016). https://doi.org/10.1117/1.JRS.10.035017

Published: 22 August 2016

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