Direction estimation using compressive array sensing and pattern reconfigurable antennas

K. R. Schab, E. L. Daly, Jennifer Truman Bernhard

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

Abstract

In many situations it is desirable to identify the direction of arrival (DoA) of an incoming signal. Recently the idea of compressive sensing have been applied to DoA problems using sub-sampled linear arrays of omnidirectional antennas. In this paper we explore DoA estimation with compressive sensing using antennas with diverse and reconfigurable patterns. Our results show that compressively-sampled arrays using pattern-reconfigurable antennas may meet or even exceed the accuracy of traditional DoA arrays as well as static compressed arrays of comparable size and complexity. Furthermore, we show that for arrays with lower number of elements, the degradation in performance of a compressive array can be mitigated by including pattern reconfigurable antenna elements.

Original languageEnglish (US)
Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages927-930
Number of pages4
ISBN (Print)9781479923908
DOIs
StatePublished - Jan 1 2013
Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 3 2013Nov 6 2013

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other2013 47th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period11/3/1311/6/13

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Schab, K. R., Daly, E. L., & Bernhard, J. T. (2013). Direction estimation using compressive array sensing and pattern reconfigurable antennas. In Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers (pp. 927-930). [6810424] (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2013.6810424