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      SAR image reconstruction by expectation maximization based matching pursuit

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      Author(s)
      Ugur, S.
      Arıkan, Orhan
      Gürbüz, A. C.
      Date
      2015
      Source Title
      Digital Signal Processing: A Review Journal
      Print ISSN
      1051-2004
      Publisher
      Academic Press
      Volume
      37
      Issue
      1
      Pages
      75 - 84
      Language
      English
      Type
      Article
      Item Usage Stats
      128
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      97
      downloads
      Abstract
      Synthetic Aperture Radar (SAR) provides high resolution images of terrain and target reflectivity. SAR systems are indispensable in many remote sensing applications. Phase errors due to uncompensated platform motion degrade resolution in reconstructed images. A multitude of autofocusing techniques has been proposed to estimate and correct phase errors in SAR images. Some autofocus techniques work as a post-processor on reconstructed images and some are integrated into the image reconstruction algorithms. Compressed Sensing (CS), as a relatively new theory, can be applied to sparse SAR image reconstruction especially in detection of strong targets. Autofocus can also be integrated into CS based SAR image reconstruction techniques. However, due to their high computational complexity, CS based techniques are not commonly used in practice. To improve efficiency of image reconstruction we propose a novel CS based SAR imaging technique which utilizes recently proposed Expectation Maximization based Matching Pursuit (EMMP) algorithm. EMMP algorithm is greedy and computationally less complex enabling fast SAR image reconstructions. The proposed EMMP based SAR image reconstruction technique also performs autofocus and image reconstruction simultaneously. Based on a variety of metrics, performance of the proposed EMMP based SAR image reconstruction technique is investigated. The obtained results show that the proposed technique provides high resolution images of sparse target scenes while performing highly accurate motion compensation.
      Keywords
      Autofocus
      Compressed sensing
      Expectation maximization based matching
      Pursuit algorithm
      Algorithms
      Channel estimation
      Computational complexity
      Errors
      Image matching
      Imaging techniques
      Maximum principle
      Motion compensation
      Remote sensing
      Synthetic aperture radar
      Auto-focus
      Autofocus techniques
      Autofocusing techniques
      Expectation - maximizations
      High resolution image
      Image reconstruction algorithm
      Matching pursuit algorithms
      Remote sensing applications
      Image reconstruction
      Permalink
      http://hdl.handle.net/11693/23059
      Published Version (Please cite this version)
      http://dx.doi.org/10.1016/j.dsp.2014.11.001
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      • Department of Electrical and Electronics Engineering 3702
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