New Algorithms and Sparse Regularization for Synthetic Aperture Radar Imaging

Abstract

The PI and his collaborators proposed an algorithm to form a synthetic aperture radar (SAR) image in low algorithmic complexity. It is based on the so-called butterfly scheme. Control over the accuracy is provided. Speedups in the hundreds are reported on the Air Force's GOTCHA dataset. The PI and his collaborators also investigated the possibility of forming super-resolved images from bandlimited pulse-echo data with ideas of sparse optimization that bear a link to compressed sensing. The difficulty of super-resolution is summarized in a single number, a principal angle between subspaces, which also governs the algorithmic complexity of the minimization.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2013
Accession Number
ADA580544

Entities

People

  • Laurent Demanet

Organizations

  • Massachusetts Institute of Technology

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Compressed Sensing
  • Heuristic Methods
  • Lepidoptera
  • Mathematics
  • Optimization
  • Radar
  • Radar Imaging
  • Synthetic Aperture Radar

Readers

  • Distributed Systems and Data Platform Development
  • Image Processing and Computer Vision.
  • Radar Systems Engineering.