Analysis and design of algorithms for compressive sensing based noise radar systems

Mahesh C. Shastry, Yangsoo Kwon, Ram M. Narayanan, Muralidhar Rangaswamy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We study the compressive radar imaging problem from the perspective of statistical estimation. The goal of this paper is to characterize the estimation error. Conventional radar estimation and detection techniques are characterized by concrete performance guarantees which relate directly to practical systems. The state evolution approach applied to compressive sensing is particularly useful for such analysis. We emphasize the importance of the uniform norm of the estimation error for radar imaging. In the second part of the paper, we propose a weighted compressive sampling scheme for noise radar imaging that utilizes prior information about the target scene. The weights are obtained using the mutual information estimation between target echoes and the transmitted signals with an energy constraint.

Original languageEnglish (US)
Title of host publication2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012
Pages333-336
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012 - Hoboken, NJ, United States
Duration: Jun 17 2012Jun 20 2012

Publication series

NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)2151-870X

Other

Other2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012
Country/TerritoryUnited States
CityHoboken, NJ
Period6/17/126/20/12

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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