Multi-source estimation consistency for improved multiple direction-of-arrival estimation
File(s)
Accepted version
Author(s)
Hafezi, S
Moore, AH
Naylor, PA
Type
Conference Paper
Abstract
In Direction-of-Arrival (DOA) estimation for multiple sources, removal of noisy data points from a set of local DOA estimates increases the resulting estimation accuracy, especially when there are many sources and they have small angular separation. In this work, we propose a post-processing technique for the enhancement of DOA extraction from a set of local estimates using the consistency of these estimates within the time frame based on adaptive multi-source assumption. Simulations in a realistic reverberant environment with sensor noise and up to 5 sources demonstrate that the proposed technique outperforms the baseline and state-of-the-art approaches. In these tests the proposed technique had the worst average error of 9°, robustness of 5° to widely varying source separation and 3° to number of sources.
Date Issued
2017-04-13
Date Acceptance
2017-01-23
Citation
2017 Hands-free Speech Communications and Microphone Arrays (HSCMA), 2017, pp.81-85
Publisher
IEEE
Start Page
81
End Page
85
Journal / Book Title
2017 Hands-free Speech Communications and Microphone Arrays (HSCMA)
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Commission of the European Communities
Grant Number
609465
Source
Joint Workshop on Hands-free Speech Communication and Microphone Arrays
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Telecommunications
Engineering
direction-of-arrival estimation
k-means clustering
estimation consistency
direct-path-dominance
Publication Status
Published
Start Date
2017-03-01
Finish Date
2017-03-03
Coverage Spatial
San Francisco, USA
Date Publish Online
2017-04-13