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DTSTART:20200308T030000
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DTSTART:20191103T010000
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DTSTAMP:20191125T043945Z
UID:E1B684B3-C423-455E-9470-E01A4370965E
DTSTART;TZID=US/Central:20191115T140000
DTEND;TZID=US/Central:20191115T150000
DESCRIPTION:Inverse synthetic aperture radar (ISAR) imaging is a powerful t
 ool for analyzing radar cross-section (RCS) measurements of complex target
 s. In particular\, the ability to extract portions of an ISAR image and re
 construct their associated RCS can provide insight into the individual sca
 ttering sources comprising the target’s signature\, as well as the abili
 ty to remove undesired contamination such as clutter and noise from the da
 ta. Unfortunately\, while analytically elegant and computationally efficie
 nt\, conventional ISAR image edit and reconstruction (IER) techniques suff
 er from errors in the predicted RCS due to “edge effects” from the edi
 ting masks\, particularly when the target’s scattering sources are not w
 ell-resolved or when the contamination is smeared throughout the image. In
  this talk\, we present the use of the basis pursuit (BP) L1 minimization 
 technique to overcome these and other shortcomings of conventional ISAR IE
 R techniques. We begin with a review of the RCS measurements and ISAR imag
 ing\, followed by a brief discussion of L1 minimization and its ability to
  find “sparse” representations for measured data. This is followed by 
 examples of how the application of BP to ISAR measurements can provide enh
 anced RCS reconstruction of individual target scattering sources and impro
 ved isolation of contamination from undesired error sources.\n\nCo-sponsor
 ed by: Department of Electrical and Computer Engineering\, University of I
 llinois at Chicago\n\nSpeaker(s): Ivan J. LaHaie\, Ph.D.\, \n\nBldg: 317 B
 urnham Hall\, 804 South Halsted St\, Chicago\, Illinois\, United States\, 
 60607-7053
LOCATION:Bldg: 317 Burnham Hall\, 804 South Halsted St\, Chicago\, Illinois
 \, United States\, 60607-7053
ORGANIZER:derric1@uic.edu
SEQUENCE:4
SUMMARY:Application of L1 Minimization Techniques to Radar Cross-Section Di
 agnostic Imaging and Error Mitigation
URL;VALUE=URI:https://events.vtools.ieee.org/m/209567
X-ALT-DESC:Description: <br /><p>Inverse synthetic aperture radar (ISAR) im
 aging is a powerful tool for analyzing radar cross-section (RCS) measureme
 nts of complex targets. In particular\, the ability to extract portions of
  an ISAR image and reconstruct their associated RCS can provide insight in
 to the individual scattering sources comprising the target&rsquo\;s signat
 ure\, as well as the ability to remove undesired contamination such as clu
 tter and noise from the data. Unfortunately\, while analytically elegant a
 nd computationally efficient\, conventional ISAR image edit and reconstruc
 tion (IER) techniques suffer from errors in the predicted RCS due to &ldqu
 o\;edge effects&rdquo\; from the editing masks\, particularly when the tar
 get&rsquo\;s scattering sources are not well-resolved or when the contamin
 ation is smeared throughout the image. In this talk\, we present the use o
 f the basis pursuit (BP) L1 minimization technique to overcome these and o
 ther shortcomings of conventional ISAR IER techniques. We begin with a rev
 iew of the RCS measurements and ISAR imaging\, followed by a brief discuss
 ion of L1 minimization and its ability to find &ldquo\;sparse&rdquo\; repr
 esentations for measured data. This is followed by examples of how the app
 lication of BP to ISAR measurements can provide enhanced RCS reconstructio
 n of individual target scattering sources and improved isolation of contam
 ination from undesired error sources.</p>
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