Multi-source localization using a DOA Kernel based spatial covariance model and complex nonnegative matrix factorization

J. J. Carabias-Orti, P. Cabanas-Molero, P. Vera-Candeas, J. Nikunen

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

    2 Citations (Scopus)

    Abstract

    This paper presents an algorithm for multiple source localization using a beamforming-inspired spatial covariance model (SCM) and complex non-negative matrix factorization (CNMF). In this work, we assume that the source signals are known in advance whereas the mixing filter is modeled by the weighted sum of direction of arrival (DOA) kernels which encode the phase and the amplitude differences between microphones for every possible source direction. The direction of arrival (i.e. azimuth and elevation) for each source is estimated using CNMF. The proposed system is evaluated for DOA estimation task using two datasets covering a large number of configurations (number of channels, number of simultaneous sources, reverberation time, microphones spacing, source types and angular positions of the sources). Finally, a comparison to other state-of-the-art methods is performed, showing the robustness of the proposed method.

    Original languageEnglish
    Title of host publication2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018
    PublisherIEEE
    Pages440-444
    Number of pages5
    ISBN (Print)9781538647523
    DOIs
    Publication statusPublished - 27 Aug 2018
    Publication typeA4 Article in conference proceedings
    EventIEEE Sensor Array and Multichannel Signal Processing Workshop - Sheffield, United Kingdom
    Duration: 8 Jul 201811 Jul 2018

    Publication series

    NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
    ISSN (Print)1551-2282
    ISSN (Electronic)2151-870X

    Conference

    ConferenceIEEE Sensor Array and Multichannel Signal Processing Workshop
    Abbreviated titleSAM
    Country/TerritoryUnited Kingdom
    CitySheffield
    Period8/07/1811/07/18

    Keywords

    • Direction of arrival
    • Nonnegative matrix factorization
    • Source localization
    • Spatial covariance matrix
    • Time difference of arrival

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

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

    Fingerprint

    Dive into the research topics of 'Multi-source localization using a DOA Kernel based spatial covariance model and complex nonnegative matrix factorization'. Together they form a unique fingerprint.

    Cite this