Distributed MIMO radar using compressive sampling

Athina P. Petropulu, Yao Yu, H. Vincent Poor

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

25 Scopus citations

Abstract

A distributed MIMO radar is considered, in which the transmit and receive antennas belong to nodes of a small scale wireless network. The transmit waveforms could be uncorrelated, or correlated in order to achieve a desirable beampattern. The concept of compressive sampling is employed at the receive nodes in order to perform direction of arrival (DOA) estimation. According to the theory of compressive sampling, a signal that is sparse in some domain can be recovered based on far fewer samples than required by the Nyquist sampling theorem. The DOAs of targets form a sparse vector in the angle space, andtherefore, compressive sampling can be applied for DOA estimation. The proposed approach achieves the superior resolution of MIMO radar with far fewer samples than other approaches. This is particularly useful in a distributed scenario, in which the results at each receive node need to be transmitted to a fusion center.

Original languageEnglish (US)
Title of host publication2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Pages203-207
Number of pages5
DOIs
StatePublished - Dec 1 2008
Event2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008 - Pacific Grove, CA, United States
Duration: Oct 26 2008Oct 29 2008

Publication series

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

Other

Other2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
CountryUnited States
CityPacific Grove, CA
Period10/26/0810/29/08

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

Keywords

  • Compressive sampling
  • DOA estimation
  • MIMO radar

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    Petropulu, A. P., Yu, Y., & Poor, H. V. (2008). Distributed MIMO radar using compressive sampling. In 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008 (pp. 203-207). [5074392] (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2008.5074392