Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)

Two-Stage Near-Field Source Localization Using Acoustic Vector Sensor

Authors
Dawei Xiao, Jinfang Cheng, Chaoran Zhang
Corresponding Author
Dawei Xiao
Available Online October 2016.
DOI
10.2991/ceie-16.2017.42How to use a DOI?
Keywords
Near-Field; Localization; Acoustic Vector Sensor; Two-Stage
Abstract

To avoid 2-D search, a two-stage algorithm for passively estimating the azimuth and range of a near-field source using an acoustic vector sensor is proposed. This algorithm utilizes two particle velocity channels to estimate the azimuth, and then combines the pressure channel to estimate the range. The Cram,r-Rao bound (CRB) on the estimation errors of the source azimuth is derived. Compared with the traditional method and CRB, The proposed algorithm is computationally efficient and has the similar performance with 2-D MUSIC algorithm. Simulation results are provided to demonstrate the high-efficient quality of this method.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
10.2991/ceie-16.2017.42
ISSN
2352-5401
DOI
10.2991/ceie-16.2017.42How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Dawei Xiao
AU  - Jinfang Cheng
AU  - Chaoran Zhang
PY  - 2016/10
DA  - 2016/10
TI  - Two-Stage Near-Field Source Localization Using Acoustic Vector Sensor
BT  - Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
PB  - Atlantis Press
SP  - 333
EP  - 340
SN  - 2352-5401
UR  - https://doi.org/10.2991/ceie-16.2017.42
DO  - 10.2991/ceie-16.2017.42
ID  - Xiao2016/10
ER  -