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Tracking and Sensor Fusion in Direction of Arrival Estimation Using Optimal Mass Transport

Elvander, Filip LU ; Haasler, Isabel ; Jakobsson, Andreas LU orcid and Karlsson, Johan (2018) 26th European Signal Processing Conference, EUSIPCO 2018 p.1631-1635
Abstract
In this work, we propose new methods for information fusion and tracking in direction of arrival (DOA) estimation by utilizing an optimal mass transport framework. Sensor array measurements in DOA estimation may not be consistent due to misalignments and calibration errors. By using optimal mass transport as a notion of distance for combining the information obtained from all the sensor arrays, we obtain an approach that can prevent aliasing and is robust to array misalignments. For the case of sequential tracking, the proposed method updates the DOA estimate using the new measurements and an optimal mass transport prior. In the case of sensor fusion, information from several, individual, sensor arrays is combined using a barycenter... (More)
In this work, we propose new methods for information fusion and tracking in direction of arrival (DOA) estimation by utilizing an optimal mass transport framework. Sensor array measurements in DOA estimation may not be consistent due to misalignments and calibration errors. By using optimal mass transport as a notion of distance for combining the information obtained from all the sensor arrays, we obtain an approach that can prevent aliasing and is robust to array misalignments. For the case of sequential tracking, the proposed method updates the DOA estimate using the new measurements and an optimal mass transport prior. In the case of sensor fusion, information from several, individual, sensor arrays is combined using a barycenter formulation of optimal mass transport. (Less)
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author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
26th European Signal Processing Conference, EUSIPCO 2018
pages
5 pages
publisher
European Association for Signal Processing (EURASIP)
conference name
26th European Signal Processing Conference, EUSIPCO 2018
conference location
Rome, Italy
conference dates
2018-09-03 - 2018-09-07
external identifiers
  • scopus:85059812841
ISBN
978-90-827970-1-5
DOI
10.23919/EUSIPCO.2018.8553068
language
English
LU publication?
yes
id
2471de5e-e0a9-43ad-aefe-85593b7e61b1
date added to LUP
2018-09-12 13:51:25
date last changed
2022-04-25 08:55:53
@inproceedings{2471de5e-e0a9-43ad-aefe-85593b7e61b1,
  abstract     = {{In this work, we propose new methods for information fusion and tracking in direction of arrival (DOA) estimation by utilizing an optimal mass transport framework. Sensor array measurements in DOA estimation may not be consistent due to misalignments and calibration errors. By using optimal mass transport as a notion of distance for combining the information obtained from all the sensor arrays, we obtain an approach that can prevent aliasing and is robust to array misalignments. For the case of sequential tracking, the proposed method updates the DOA estimate using the new measurements and an optimal mass transport prior. In the case of sensor fusion, information from several, individual, sensor arrays is combined using a barycenter formulation of optimal mass transport.}},
  author       = {{Elvander, Filip and Haasler, Isabel and Jakobsson, Andreas and Karlsson, Johan}},
  booktitle    = {{26th European Signal Processing Conference, EUSIPCO 2018}},
  isbn         = {{978-90-827970-1-5}},
  language     = {{eng}},
  pages        = {{1631--1635}},
  publisher    = {{European Association for Signal Processing (EURASIP)}},
  title        = {{Tracking and Sensor Fusion in Direction of Arrival Estimation Using Optimal Mass Transport}},
  url          = {{http://dx.doi.org/10.23919/EUSIPCO.2018.8553068}},
  doi          = {{10.23919/EUSIPCO.2018.8553068}},
  year         = {{2018}},
}