Rank Properties of Manifold Matrices of Sparse Arrays

Po Chih Chen, P. P. Vaidyanathan

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

5 Scopus citations

Abstract

It is well known that the manifold matrix of a sensor array has to satisfy certain rank conditions in order for certain algorithms such as MUSIC and ESPRIT to work without creating ambiguity. For the case of sparse arrays this condition is often not satisfied, although there exist some sparse arrays which satisfy them. This paper develops the constraints on the sensor locations which allow such conditions to be satisfied. After a number of examples to develop insights, two results are given: one is a necessary and sufficient condition for two specific cases and the other is a necessary condition for the general case. The necessary condition for the general case reduces to the necessary and sufficient condition in the two specific cases. In order for sparse arrays to satisfy these conditions, it is not required that there be a uniform linear subarray with more sensors than sources.

Original languageEnglish
Title of host publication55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1628-1633
Number of pages6
ISBN (Electronic)9781665458283
DOIs
StatePublished - 2021
Event55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 - Virtual, Pacific Grove, United States
Duration: 31 Oct 20213 Nov 2021

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2021-October
ISSN (Print)1058-6393

Conference

Conference55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
Country/TerritoryUnited States
CityVirtual, Pacific Grove
Period31/10/213/11/21

Keywords

  • Ambiguities
  • DOA estimation
  • ESPRIT
  • MUSIC
  • sparse arrays

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