Direction-of-Arrival Estimation Using Gaussian Process Interpolation

Ishan D. Khurjekar, Peter Gerstoft, Christoph F. Mecklenbräuker, Zoi Heleni Michalopoulou

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

1 Scopus citations

Abstract

Gaussian processes (GP's) have been used to predict acoustic fields by interpolating under-sampled field observations. Using GP interpolation to predict fields is advantageous because of its ability to denoise measurements and for its prediction of likely field outcomes given a certain field coherence, or in GP terminology, a kernel. While there are many design options for a coherence function, in this study we focus on the radial basis function kernel for estimating the direction-of-arrival (DOA) of a plane wave impinging on a uniform linear array. We demonstrate that an array sampled with spacing larger than a half wavelength can benefit from GP interpolation, providing a smaller root mean squared error in comparison to the error of conventional beamforming for DOA estimation.

Original languageEnglish (US)
Title of host publicationICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728163277
DOIs
StatePublished - 2023
Event48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023 - Rhodes Island, Greece
Duration: Jun 4 2023Jun 10 2023

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2023-June
ISSN (Print)1520-6149

Conference

Conference48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Country/TerritoryGreece
CityRhodes Island
Period6/4/236/10/23

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • beamforming
  • Direction-of-arrival estimation
  • Gaussian processes
  • spatial aliasing

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