TY - GEN
T1 - Multi-source localization using a DOA Kernel based spatial covariance model and complex nonnegative matrix factorization
AU - Carabias-Orti, J. J.
AU - Cabanas-Molero, P.
AU - Vera-Candeas, P.
AU - Nikunen, J.
N1 - EXT="Carabias-Orti, J. J."
PY - 2018/8/27
Y1 - 2018/8/27
N2 - 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.
AB - 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.
KW - Direction of arrival
KW - Nonnegative matrix factorization
KW - Source localization
KW - Spatial covariance matrix
KW - Time difference of arrival
U2 - 10.1109/SAM.2018.8448664
DO - 10.1109/SAM.2018.8448664
M3 - Conference contribution
AN - SCOPUS:85053623218
SN - 9781538647523
T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
SP - 440
EP - 444
BT - 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018
PB - IEEE
T2 - IEEE Sensor Array and Multichannel Signal Processing Workshop
Y2 - 8 July 2018 through 11 July 2018
ER -