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Upgrade Methods for Stratified Sensor Network Self-Calibration

Larsson, M. LU orcid ; Flood, G. LU ; Oskarsson, M. LU orcid and Astrom, K. LU orcid (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:
author
; ; and
organization
publishing date
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}},
}