Using frame theoretic convolutional gridding for robust synthetic aperture sonar imaging

John McKay, Anne Gelb, Vishal Monga, Raghu G. Raj

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Recent progress in synthetic aperture sonar (SAS) technology and processing has led to significant advances in underwater imaging, outperforming previously common approaches in both accuracy and efficiency. There are, however, inherent limitations to current SAS reconstruction methodology. In particular, popular and efficient Fourier domain SAS methods require a 2D interpolation which is often ill conditioned and inaccurate, inevitably reducing robustness with regard to speckle and inaccurate sound-speed estimation. To overcome these issues, we propose using the frame theoretic convolution gridding (FTCG) algorithm to handle the non-uniform Fourier data. FTCG extends upon non-uniform fast Fourier transform (NUFFT) algorithms by casting the NUFFT as an approximation problem given Fourier frame data. The FTCG has been show to yield improved accuracy at little more computational cost. Using simulated data, we outline how the FTCG can be used to enhance current SAS processing.

Original languageEnglish (US)
Title of host publicationOCEANS 2017 � Anchorage
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9780692946909
StatePublished - Dec 19 2017
EventOCEANS 2017 - Anchorage - Anchorage, United States
Duration: Sep 18 2017Sep 21 2017

Publication series

NameOCEANS 2017 - Anchorage


OtherOCEANS 2017 - Anchorage
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Oceanography
  • Automotive Engineering
  • Water Science and Technology
  • Acoustics and Ultrasonics
  • Instrumentation
  • Ocean Engineering


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