Optimization Methods for Synthetic Aperture Radar Imaging

Chapter

Abstract

We review recent developments in Synthetic Aperture Radar (SAR) image formation from an optimization perspective. Majority of these methods can be viewed as constrained least squares problems exploiting sparsity. We reviewed analytic and large scale numerical optimization based approaches in both deterministic and Bayesian frameworks. These methods offer substantial improvements in image quality, suppression of noise and clutter. Analytic methods also have the advantage of computational efficiency.

Notes

Acknowledgements

This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-16-1-0234, and by the National Science Foundation (NSF) under Grant No. CCF-1421496.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Electrical, Computer and Systems EngineeringRensselaer Polytechnic InstituteTroyUSA
  2. 2.Department of Electronics and Communications EngineeringIstanbul Technical UniversityMaslakTurkey

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