Non-Coherent Sensor Fusion via Entropy Regularized Optimal Mass Transport
Elvander, Filip LU ; Haasler, Isabel ; Jakobsson, Andreas LU
and Karlsson, Johan
(2019)
IEEE International Conference on Acoustics, Speech, and Signal Processing 2019
p.4415-4419
- Abstract
- This work presents a method for information fusion in source localization applications. The method utilizes the concept of optimal mass transport in order to construct estimates of the spatial spectrum using a convex barycenter formulation. We introduce an entropy regularization term to the convex objective, which allows for low-complexity iterations of the solu- tion algorithm and thus makes the proposed method applicable also to higher-dimensional problems. We illustrate the proposed method’s inherent robustness to misalignment and miscalibration of the sensor arrays using numerical examples of localization in two dimensions.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/9d8b09e6-4bfa-4fe3-852c-2362db372599
- author
- Elvander, Filip
LU
; Haasler, Isabel
; Jakobsson, Andreas
LU
and Karlsson, Johan
- organization
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- optimal mass transport, entropy regularization, target localization, non-coherent processing
- host publication
- Acoustics, Speech and Signal Processing (ICASSP), 2019 IEEE International Conference on
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE International Conference on Acoustics, Speech, and Signal Processing 2019
- conference location
- Brighton, United Kingdom
- conference dates
- 2019-05-13 - 2019-05-17
- external identifiers
-
- scopus:85069002151
- ISBN
- 978-1-4799-8131-1
- DOI
- 10.1109/ICASSP.2019.8682186
- language
- English
- LU publication?
- yes
- id
- 9d8b09e6-4bfa-4fe3-852c-2362db372599
- date added to LUP
- 2019-05-29 09:17:00
- date last changed
- 2022-04-26 00:37:06
@inproceedings{9d8b09e6-4bfa-4fe3-852c-2362db372599,
abstract = {{This work presents a method for information fusion in source localization applications. The method utilizes the concept of optimal mass transport in order to construct estimates of the spatial spectrum using a convex barycenter formulation. We introduce an entropy regularization term to the convex objective, which allows for low-complexity iterations of the solu- tion algorithm and thus makes the proposed method applicable also to higher-dimensional problems. We illustrate the proposed method’s inherent robustness to misalignment and miscalibration of the sensor arrays using numerical examples of localization in two dimensions.}},
author = {{Elvander, Filip and Haasler, Isabel and Jakobsson, Andreas and Karlsson, Johan}},
booktitle = {{Acoustics, Speech and Signal Processing (ICASSP), 2019 IEEE International Conference on}},
isbn = {{978-1-4799-8131-1}},
keywords = {{optimal mass transport; entropy regularization; target localization; non-coherent processing}},
language = {{eng}},
pages = {{4415--4419}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Non-Coherent Sensor Fusion via Entropy Regularized Optimal Mass Transport}},
url = {{http://dx.doi.org/10.1109/ICASSP.2019.8682186}},
doi = {{10.1109/ICASSP.2019.8682186}},
year = {{2019}},
}