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AN AUTOMATIC SYSTEM FOR MICROPHONE SELF-LOCALIZATION USING AMBIENT SOUND

Simayijiang, Zhayida LU ; Andersson, Fredrik LU ; Kuang, Yubin LU and Åström, Karl LU (2014) 22nd European Signal Processing Conference - In European Signal Processing Conference
Abstract
In this paper, we develop a system for microphone selflocalization

based on ambient sound, without any assumptions

on the 3D locations of the microphones and sound

sources. We aim at developing a system capable of dealing

with multiple moving sound sources. We will show that this

is possible given that there are instances where there are only

one dominating sound source. In the first step of the system

we employ a feature detection and matching strategy. This

produces TDOA data, possibly with missing data and with

outliers. Then we use a robust and stratified approach for the

parameter estimation. We use robust techniques to calculate

initial... (More)
In this paper, we develop a system for microphone selflocalization

based on ambient sound, without any assumptions

on the 3D locations of the microphones and sound

sources. We aim at developing a system capable of dealing

with multiple moving sound sources. We will show that this

is possible given that there are instances where there are only

one dominating sound source. In the first step of the system

we employ a feature detection and matching strategy. This

produces TDOA data, possibly with missing data and with

outliers. Then we use a robust and stratified approach for the

parameter estimation. We use robust techniques to calculate

initial estimates on the offsets parameters, followed by nonlinear

optimization based on a rank criterion. Sequentially

we use robust methods for calculating initial estimates of the

sound source positions and microphone positions, followed

by non-linear Maximum Likelihood estimation of all parameters.

The methods are tested and verified using anechoic

chamber sound recordings. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
European Signal Processing Conference
pages
5 pages
publisher
EURASIP
conference name
22nd European Signal Processing Conference -
external identifiers
  • scopus:84911886303
ISSN
2219-5491
language
English
LU publication?
yes
id
82f411f8-8a32-4b8b-bed9-4922e022a4e6 (old id 4589486)
date added to LUP
2014-09-17 11:58:02
date last changed
2017-03-05 03:42:52
@inproceedings{82f411f8-8a32-4b8b-bed9-4922e022a4e6,
  abstract     = {In this paper, we develop a system for microphone selflocalization<br/><br>
based on ambient sound, without any assumptions<br/><br>
on the 3D locations of the microphones and sound<br/><br>
sources. We aim at developing a system capable of dealing<br/><br>
with multiple moving sound sources. We will show that this<br/><br>
is possible given that there are instances where there are only<br/><br>
one dominating sound source. In the first step of the system<br/><br>
we employ a feature detection and matching strategy. This<br/><br>
produces TDOA data, possibly with missing data and with<br/><br>
outliers. Then we use a robust and stratified approach for the<br/><br>
parameter estimation. We use robust techniques to calculate<br/><br>
initial estimates on the offsets parameters, followed by nonlinear<br/><br>
optimization based on a rank criterion. Sequentially<br/><br>
we use robust methods for calculating initial estimates of the<br/><br>
sound source positions and microphone positions, followed<br/><br>
by non-linear Maximum Likelihood estimation of all parameters.<br/><br>
The methods are tested and verified using anechoic<br/><br>
chamber sound recordings.},
  author       = {Simayijiang, Zhayida and Andersson, Fredrik and Kuang, Yubin and Åström, Karl},
  booktitle    = {European Signal Processing Conference},
  issn         = {2219-5491},
  language     = {eng},
  pages        = {5},
  publisher    = {EURASIP},
  title        = {AN AUTOMATIC SYSTEM FOR MICROPHONE SELF-LOCALIZATION USING AMBIENT SOUND},
  year         = {2014},
}