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SAR minimum entropy autofocusing based on Prewitt operator

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  • Xiaoze Hou
  • Yanheng Ma

Abstract

Current autofocus algorithms utilizing image criteria impose a significant computational burden. Therefore, this paper proposes a computationally efficient autofocus algorithm combined with SAR image feature points, employing the Prewitt operator to obtain the SAR image features. The range cell with the number of feature points in the front row as the input of the autofocus method to perform motion error estimation and compensation on SAR imagery. Our method’s key feature is to optimize the selection criteria of range cells by acquiring the feature points of SAR images,reduces the number of input range cell,reduce the computational complexity of the autofocus algorithm and ultimately enhance the focusing effect of SAR images. Trials involving simulation and measured data demonstrate the effectiveness of the developed method.

Suggested Citation

  • Xiaoze Hou & Yanheng Ma, 2023. "SAR minimum entropy autofocusing based on Prewitt operator," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-20, February.
    • Handle: RePEc:plo:pone00:0276051
    DOI: 10.1371/journal.pone.0276051
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