MCA: A multichannel approach to SAR autofocus

Robert L. Morrison, Minh N. Do, David C. Munson

Research output: Contribution to journalArticlepeer-review


We present a new noniterative approach to synthetic aperture radar (SAR) autofocus, termed the multichannel autofocus (MCA) algorithm. The key in the approach is to exploit the multichannel redundancy of the defocusing operation to create a linear subspace, where the unknown perfectly focused image resides, expressed in terms of a known basis formed from the given defocused image. A unique solution for the perfectly focused image is then directly determined through a linear algebraic formulation by invoking an additional image support condition. The MCA approach is found to be computationally efficient and robust and does not require prior assumptions about the SAR scene used in existing methods. In addition, the vector-space formulation of MCA allows sharpness metric optimization to be easily incorporated within the restoration framework as a regularization term. We present experimental results characterizing the performance of MCA in comparison with conventional autofocus methods and discuss the practical implementation of the technique.

Original languageEnglish (US)
Pages (from-to)840-853
Number of pages14
JournalIEEE Transactions on Image Processing
Issue number4
StatePublished - 2009


  • Blind deconvolution
  • Circular deconvolution
  • Image restoration
  • Multichannel
  • Sharpness optimization
  • Signal subspace methods
  • Synthetic aperture radar (SAR) autofocus

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software


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