Volume 7 Issue 4
Aug.  2018
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Zhao Bo, Huang Lei, Zhou Hanfei, Zhang Liang, Li Qiang, Huang Min. 1-bit SAR Imaging Method Based on Single-frequency Time-varying Threshold[J]. Journal of Radars, 2018, 7(4): 446-454. doi: 10.12000/JR18036
Citation: Zhao Bo, Huang Lei, Zhou Hanfei, Zhang Liang, Li Qiang, Huang Min. 1-bit SAR Imaging Method Based on Single-frequency Time-varying Threshold[J]. Journal of Radars, 2018, 7(4): 446-454. doi: 10.12000/JR18036

1-bit SAR Imaging Method Based on Single-frequency Time-varying Threshold

doi: 10.12000/JR18036
Funds:  The National Natural Science Foundation of China (U1713217, 61501485, 61501300, 61601300, 61601304), The China Postdoctoral Science Foundation (2015M582413, 2017M610547), The Natural Science foundation of Guangdong Province, China (2015A030311030), The Foundation of Shenzhen City (ZDSYS201507081625213, JCYJ20160520165659418, JCYJ20170302142545828, JCYJ20150324140036835), The Shenzhen University (201557, 2016057)
  • Received Date: 2018-04-28
  • Rev Recd Date: 2018-06-25
  • Publish Date: 2018-08-28
  • This paper proposes a 1-bit Synthetic Aperture Radar (SAR) imaging method based on a single-frequency time-varying threshold. Synthetic aperture radar echoes are quantized to 1-bit sampling data by comparing the data with the threshold; this reduces the data-width of the SAR echoes, consequently simplifying the system and improving efficiency. The conventional 1-bit sampling compares the signal to a zero threshold, bringing nonlinear distortion to the relative amplitude and degrading the imaging quality. The random threshold can keep the amplitude information, but it introduces additional noise-like interferences. In contrary, the single-frequency time-varying threshold can maintain the amplitude information lost during the 1-bit sampling and quantization, and at the same time, eliminate noise-like interferences; thus, the imaging quality of SAR using 1-bit sampling and quantization can be improved. The focusing quality and the amplitude-maintaining ability of the proposed approach is quantitatively analyzed, and the effectiveness of the approach is verified by an imaging experiment on a scene.

     

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