TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

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

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018
KustantajaIEEE
Sivut440-444
Sivumäärä5
ISBN (painettu)9781538647523
DOI - pysyväislinkit
TilaJulkaistu - 27 elokuuta 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE Sensor Array and Multichannel Signal Processing Workshop - Sheffield, Iso-Britannia
Kesto: 8 heinäkuuta 201811 heinäkuuta 2018

Julkaisusarja

NimiProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (painettu)1551-2282
ISSN (elektroninen)2151-870X

Conference

ConferenceIEEE Sensor Array and Multichannel Signal Processing Workshop
LyhennettäSAM
MaaIso-Britannia
KaupunkiSheffield
Ajanjakso8/07/1811/07/18

Tiivistelmä

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.