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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:
author
organization
publishing date
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
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
2020-01-16 03:57:16
@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},
  language     = {eng},
  pages        = {4415--4419},
  publisher    = {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},
}