Improving compressive sensing results in radar using multiple reconstructions

Gregory Wilsenach, Amit Kumar Mishra

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)


Compressive sensing based reconstruction introduces noise which is dependent on a number of factors, in particular the choice of representation basis. In this paper we show how multiple reconstructions using different bases can be used to more accurately retrieve target information in a radar signal. We focus on signal averaging as a technique for achieving these improvements, and discuss the effectiveness of this strategy as well as a few potential problems and limitations inherent in such a strategy. We also provide a basic example of a way of improving this averaging technique, and provide a template for further development and case-by-case fine tuning.

Original languageEnglish
Title of host publication2014 IEEE Radar Conference
Subtitle of host publicationFrom Sensing to Information, RadarCon 2014
PublisherIEEE Press
Number of pages5
ISBN (Electronic)978-1-4799-2035-8
Publication statusPublished - 19 May 2014
Externally publishedYes
Event2014 IEEE Radar Conference, RadarCon 2014 - Cincinnati, OH, United States of America
Duration: 19 May 201423 May 2014

Publication series

NameIEEE National Radar Conference - Proceedings
ISSN (Print)1097-5659


Conference2014 IEEE Radar Conference, RadarCon 2014
Country/TerritoryUnited States of America
CityCincinnati, OH
Period19 May 201423 May 2014


  • Compressive Sensing
  • Multiple Reconstruction
  • Radar
  • Signal Averaging
  • Wavelet


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