Spatio-spectral masking for spherical array beamforming

Uri Abend, Boaz Rafaely

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

4 Scopus citations

Abstract

Beamforming using spherical arrays has become increasingly popular in recent years. However, the performance of beamforming algorithms is greatly affected by the limited number of sensors. This work offers a novel approach based on pre-processing of the spatial data in order to better separate the signal from noise, thus improving beamforming performance. The method involves transformation of the data to the spatio-spectral domain, using the spatially-localized spherical Fourier transform, followed by masking. The masking function is defined using a-priori knowledge of signal to noise ratio. The performance of the proposed algorithm is then evaluated using a simulation study, showing improvement over conventional spatial filtering.

Original languageEnglish
Title of host publication2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781509021529
DOIs
StatePublished - 4 Jan 2017
Event2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 - Eilat, Israel
Duration: 16 Nov 201618 Nov 2016

Publication series

Name2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Conference

Conference2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Country/TerritoryIsrael
CityEilat
Period16/11/1618/11/16

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Artificial Intelligence
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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