Adaptive Beamforming Based on Interference Covariance Matrix Estimation

Yujie Gu, Yimin D. Zhang

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

11 Scopus citations

Abstract

In this paper, we propose a robust adaptive beam-forming algorithm, where the interference-plus-noise covariance matrix is estimated by identifying and removing the desired signal component from the sample covariance matrix. For this purpose, we construct a desired signal subspace and its orthogonal subspace to identify the eigenvector of the sample covariance matrix corresponding to the desired signal. The adaptive beam-former is then designed using the estimated interference-plus-noise covariance matrix and the identified signal eigenvector. Because both are independent of the knowledge of the array geometry, the proposed adaptive beamformer is robust to array model mismatch. Simulation results demonstrate the effectiveness of the proposed robust adaptive beamforming algorithm.

Original languageEnglish
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages619-623
Number of pages5
ISBN (Electronic)9781728143002
DOIs
StatePublished - Nov 2019
Externally publishedYes
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: 3 Nov 20196 Nov 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
Country/TerritoryUnited States
CityPacific Grove
Period3/11/196/11/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Adaptive beamforming
  • interference-plus-noise covariance matrix estimation
  • robust beamforming
  • signal identification.

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