Large region acoustic source mapping: A generalized sparse constrained deconvolution approach

Shengkui Zhao, Cagdas Tuna, Thi Ngoc Tho Nguyen, Douglas L. Jones

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

Abstract

This paper presents a generalized multiple-point sparse constrained deconvolution approach for mapping acoustic noise sources in large regions using a movable array. Extended from our previous MPSC-DAMAS approach, we first derive a generalized inverse problem relating to the source powers and the array manifold using a generic beamformer and an explicit measurement noise model. We then propose a generalized MPSC-DAMAS (GMPSC-DAMAS) approach for resolving the inverse problem. A new parameter setting method based on a multiple-point minimum-variance-distortionless-response (MVDR) beamformer is also presented. The realizations of the GMPSC-DAMAS approach using the delay- and-sum (DAS) beamformer and the MVDR beamformer are evaluated. Simulation results show the proposed GMPSC-DAMAS approach achieves much lower absolute power estimation errors and processing time than the MPSC-DAMAS approach in terms of number of sources and robustness to measurement noise.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3186-3190
Number of pages5
ISBN (Electronic)9781479999880
DOIs
StatePublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2016-May
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period3/20/163/25/16

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Keywords

  • acoustic source mapping
  • beamformer
  • microphone arrays
  • source localization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Zhao, S., Tuna, C., Nguyen, T. N. T., & Jones, D. L. (2016). Large region acoustic source mapping: A generalized sparse constrained deconvolution approach. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (pp. 3186-3190). [7472265] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7472265