Sparsity and compressive sensing of sense-through-foliage radar signals

Qilian Liang*, Ji Wu, Xiuzhen Cheng, Dechang Chen, Jing Liang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Motivated by recent advances on Compressive Sensing (CS), we study the sparsity of sense-through-foliage radar signals. Based on CLEAN method, we obtain the impulse response for sense-through-foliage communication channels for three different radars, 200MHz, 400MHz, and UWB radars. Channel impulse responses for the above three different kinds of channels demonstrate that the sense-through-foliage signals are very sparse, which means CS is possible to be applied to sense-through-foliage radar signals to tremendously reduce the sampling rate. We apply CS and linear programming to sparse signal compression and recovery, and it turns out that we could achieve compression ratio of 32:1 with perfect recovery for the UWB radar signals.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Communications, ICC 2012
Pages6376-6380
Number of pages5
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Communications, ICC 2012 - Ottawa, ON, Canada
Duration: 10 Jun 201215 Jun 2012

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607

Conference

Conference2012 IEEE International Conference on Communications, ICC 2012
Country/TerritoryCanada
CityOttawa, ON
Period10/06/1215/06/12

Keywords

  • Compressive sensing
  • UWB
  • radars
  • sense-through-foliage
  • sparsity

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