A performance-weighted blended dominant mode rejection beamformer

John R. Buck, Andrew C. Singer

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

Abstract

Adaptive beamformers operating in snapshot deficient situations often estimate regularization parameters such as the diagonal loading level or the signal subspace dimension. We propose a new beamformer that avoids this problem by computing its array weights as a mixture of the array weights for a set of beamformers. The new beamformer's average output power asymptotically approaches the best performance of any of the beamformers in the set. Applying this technique to the Dominant Mode Rejection (DMR) beamformer obviates the need to estimate the dominant signal subspace dimension. An example simulation of a complicated passive sonar scenario illustrates that the blended beamformer's performance rivals the performance of the best fixed subspace DMR beamformer, and may outperform all of them in nonstationary environments.

Original languageEnglish (US)
Title of host publication2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018
PublisherIEEE Computer Society
Pages124-128
Number of pages5
ISBN (Print)9781538647523
DOIs
StatePublished - Aug 27 2018
Event10th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2018 - Sheffield, United Kingdom
Duration: Jul 8 2018Jul 11 2018

Publication series

NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
Volume2018-July
ISSN (Electronic)2151-870X

Other

Other10th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2018
CountryUnited Kingdom
CitySheffield
Period7/8/187/11/18

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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