Research article

Developments in three-dimensional near-field imaging with FMCW radar: A comparative study

  • Received: 15 October 2020 Accepted: 30 November 2020 Published: 01 December 2020
  • The use of microwave and mm-wave imaging (MMI) is gaining significant growth due to the developments of fast and robust imaging algorithms that resonate well with the recent cost-effective hardware developments. Specifically, the combination of frequency modulated continuous wave (FMCW) radar modules and synthetic aperture radar (SAR) has been recently considered as an effective, fast, and robust near-field three-dimensional (3D) imaging technique. In this paper, we prove that two of the most recent processing developments based on the back-propagation (BP) concept and delay and sum (DAS) concept, within the context of FMCW radar, are equivalent. We also compare the performance of these techniques with the one based on the range migration (RM) algorithm using a quantitative measure called structural similarity index (SSIM).

    Citation: Reza K. Amineh. Developments in three-dimensional near-field imaging with FMCW radar: A comparative study[J]. AIMS Electronics and Electrical Engineering, 2020, 4(4): 359-368. doi: 10.3934/ElectrEng.2020.4.359

    Related Papers:

  • The use of microwave and mm-wave imaging (MMI) is gaining significant growth due to the developments of fast and robust imaging algorithms that resonate well with the recent cost-effective hardware developments. Specifically, the combination of frequency modulated continuous wave (FMCW) radar modules and synthetic aperture radar (SAR) has been recently considered as an effective, fast, and robust near-field three-dimensional (3D) imaging technique. In this paper, we prove that two of the most recent processing developments based on the back-propagation (BP) concept and delay and sum (DAS) concept, within the context of FMCW radar, are equivalent. We also compare the performance of these techniques with the one based on the range migration (RM) algorithm using a quantitative measure called structural similarity index (SSIM).


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  • © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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