Upgrade Methods for Stratified Sensor Network Self-Calibration
(2020) 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 2020-May. p.4851-4855- Abstract
Estimating receiver and sender positions is often solved using a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. The second step can be seen as an affine upgrade. This affine upgrade is the focus of this paper. In the paper new efficient algorithms for solving for the upgrade parameters using minimal data are presented. It is also shown how to combine such solvers as initial estimates, either directly or after a hypothesis and test step, in optimization of likelihood. The system is verified on both real and synthetic data.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/6c1a49b4-1245-42c0-9059-3c86b9141ba5
- author
- Larsson, M. LU ; Flood, G. LU ; Oskarsson, M. LU and Astrom, K. LU
- organization
- publishing date
- 2020
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Calibration, Minimal Problems, RANSAC, Time-difference-of-arrival, Time-of-arrival
- host publication
- 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
- series title
- ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
- volume
- 2020-May
- article number
- 9054025
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
- conference location
- Barcelona, Spain
- conference dates
- 2020-05-04 - 2020-05-08
- external identifiers
-
- scopus:85089235732
- ISSN
- 1520-6149
- ISBN
- 9781509066315
- DOI
- 10.1109/ICASSP40776.2020.9054025
- language
- English
- LU publication?
- yes
- id
- 6c1a49b4-1245-42c0-9059-3c86b9141ba5
- date added to LUP
- 2020-08-19 07:56:50
- date last changed
- 2024-02-01 02:54:12
@inproceedings{6c1a49b4-1245-42c0-9059-3c86b9141ba5, abstract = {{<p>Estimating receiver and sender positions is often solved using a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. The second step can be seen as an affine upgrade. This affine upgrade is the focus of this paper. In the paper new efficient algorithms for solving for the upgrade parameters using minimal data are presented. It is also shown how to combine such solvers as initial estimates, either directly or after a hypothesis and test step, in optimization of likelihood. The system is verified on both real and synthetic data.</p>}}, author = {{Larsson, M. and Flood, G. and Oskarsson, M. and Astrom, K.}}, booktitle = {{2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings}}, isbn = {{9781509066315}}, issn = {{1520-6149}}, keywords = {{Calibration; Minimal Problems; RANSAC; Time-difference-of-arrival; Time-of-arrival}}, language = {{eng}}, pages = {{4851--4855}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}}, title = {{Upgrade Methods for Stratified Sensor Network Self-Calibration}}, url = {{http://dx.doi.org/10.1109/ICASSP40776.2020.9054025}}, doi = {{10.1109/ICASSP40776.2020.9054025}}, volume = {{2020-May}}, year = {{2020}}, }