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 -
- 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:
https://lup.lub.lu.se/record/4589486
- author
- Simayijiang, Zhayida
LU
; Andersson, Fredrik
LU
; Kuang, Yubin
LU
and Åström, Karl
LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- European Signal Processing Conference
- pages
- 5 pages
- publisher
- EURASIP
- conference name
- 22nd European Signal Processing Conference -
- conference location
- Lisbon, Portugal
- conference dates
- 2014-09-01 - 2014-09-05
- 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
- 2016-04-01 13:02:10
- date last changed
- 2022-03-29 05:12:03
@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}},
publisher = {{EURASIP}},
title = {{AN AUTOMATIC SYSTEM FOR MICROPHONE SELF-LOCALIZATION USING AMBIENT SOUND}},
url = {{https://lup.lub.lu.se/search/files/3121635/4589580}},
year = {{2014}},
}