Stochastic resolution analysis of co-prime arrays in radar

Radmilla Pribic, Mario Coutiño, Geert Leus

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)
16 Downloads (Pure)

Abstract

Resolution from co-prime arrays and from a full ULA of the size equal to the virtual size of co-prime arrays is investigated. We take into account not only the resulting beam width but also the fact that fewer measurements are acquired by co-prime arrays. This fact is relevant in compressive acquisition typical for compressive sensing. Our stochastic approach to resolution uses information distances computed from the geometrical structure of data models that is characterized by the Fisher information. The probability of resolution is assessed from a likelihood ratio test by using information distances. Based on this information-geometry approach, we compare stochastic resolution from active co-prime arrays and from the full-size ULA. This novel stochastic resolution analysis is applied in a one-dimensional angle processing. Results demonstrate the suitability in radar-resolution analysis.
Original languageEnglish
Title of host publication2016 IEEE Statistical Signal Processing Workshop (SSP)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Print)978-1-4673-7802-4
DOIs
Publication statusPublished - 25 Aug 2016
Event2016 IEEE Statistical Signal Processing Workshop (SSP) - Palma de Mallorca, Spain
Duration: 26 Jun 201629 Jun 2017
http://ssp2016.tsc.uc3m.es/

Workshop

Workshop2016 IEEE Statistical Signal Processing Workshop (SSP)
Abbreviated titleSSP 2016
CountrySpain
CityPalma de Mallorca
Period26/06/1629/06/17
Internet address

Keywords

  • radar
  • resolution
  • information geometry
  • co-prime arrays
  • compressive sensing

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