Imperial College London
Alternate

Patrick A. Naylor

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Speech & Acoustic Signal Processing
 
 
 
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Contact

 

+44 (0)20 7594 6235p.naylor Website

 
 
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Location

 

803Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Hafezi:2017:10.1109/TASLP.2017.2736067,
author = {Hafezi, S and Moore, AH and Naylor, PATRICK},
doi = {10.1109/TASLP.2017.2736067},
journal = {IEEE Transactions on Audio, Speech and Language Processing},
pages = {1956--1968},
title = {Augmented Intensity Vectors for Direction of Arrival Estimation in the Spherical Harmonic Domain},
url = {http://dx.doi.org/10.1109/TASLP.2017.2736067},
volume = {25},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Pseudointensity vectors (PIVs) provide a means of direction of arrival (DOA) estimation for spherical microphone arrays using only the zeroth and the first-order spherical harmonics. An augmented intensity vector (AIV) is proposed which improves the accuracy of PIVs by exploiting higher order spherical harmonics. We compared DOA estimation using our proposed AIVs against PIVs, steered response power (SRP) and subspace methods where the number of sources, their angular separation, the reverberation time of the room and the sensor noise level are varied. The results show that the proposed approach outperforms the baseline methods and performs at least as accurately as the state-of-the-art method with strong robustness to reverberation, sensor noise, and number of sources. In the single and multiple source scenarios tested, which include realistic levels of reverberation and noise, the proposed method had average error of 1.5 and 2, respectively.
AU  - Hafezi,S
AU  - Moore,AH
AU  - Naylor,PATRICK
DO  - 10.1109/TASLP.2017.2736067
EP  - 1968
PY  - 2017///
SN  - 1558-7916
SP  - 1956
TI  - Augmented Intensity Vectors for Direction of Arrival Estimation in the Spherical Harmonic Domain
T2  - IEEE Transactions on Audio, Speech and Language Processing
UR  - http://dx.doi.org/10.1109/TASLP.2017.2736067
UR  - http://hdl.handle.net/10044/1/56146
VL  - 25
ER  -
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