Tracking and Sensor Fusion in Direction of Arrival Estimation Using Optimal Mass Transport
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2471de5e-e0a9-43ad-aefe-85593b7e61b1
- author
- Elvander, Filip LU ; Haasler, Isabel ; Jakobsson, Andreas LU and Karlsson, Johan
- organization
- publishing date
- 2018
- 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}}, }