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Fast and robust stratified self-calibration using time-difference-of-arrival measurements

Larsson, Martin LU orcid ; Flood, Gabrielle LU ; Oskarsson, Magnus LU orcid and Åström, Kalle LU orcid (2021) IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 2021-June. p.4640-4644
Abstract

In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manner to efficiently remove outliers and find an initial estimate which is used for the subsequent step. Once a promising solution is obtained for a sufficiently large subset of the receivers and senders, the solution can be extended to the remaining receivers and senders. These steps are then combined with robust local optimization using the... (More)

In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manner to efficiently remove outliers and find an initial estimate which is used for the subsequent step. Once a promising solution is obtained for a sufficiently large subset of the receivers and senders, the solution can be extended to the remaining receivers and senders. These steps are then combined with robust local optimization using the initial inlier set and the initial estimate as a starting point. The proposed system is verified on both real and synthetic data.

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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
Minimal problems, RANSAC, Self-calibration, TDOA
host publication
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
series title
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
volume
2021-June
pages
5 pages
conference name
IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
conference location
Toronto, Canada
conference dates
2021-06-06 - 2021-06-11
external identifiers
  • scopus:85115155031
ISSN
1520-6149
ISBN
978-1-7281-7606-2
978-1-7281-7605-5
DOI
10.1109/ICASSP39728.2021.9414309
language
English
LU publication?
yes
id
6675a52a-5ed0-4350-96b8-57779e1f5306
date added to LUP
2021-10-04 16:01:34
date last changed
2024-04-20 12:20:02
@inproceedings{6675a52a-5ed0-4350-96b8-57779e1f5306,
  abstract     = {{<p>In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manner to efficiently remove outliers and find an initial estimate which is used for the subsequent step. Once a promising solution is obtained for a sufficiently large subset of the receivers and senders, the solution can be extended to the remaining receivers and senders. These steps are then combined with robust local optimization using the initial inlier set and the initial estimate as a starting point. The proposed system is verified on both real and synthetic data.</p>}},
  author       = {{Larsson, Martin and Flood, Gabrielle and Oskarsson, Magnus and Åström, Kalle}},
  booktitle    = {{International Conference on Acoustics, Speech, and Signal Processing (ICASSP)}},
  isbn         = {{978-1-7281-7606-2}},
  issn         = {{1520-6149}},
  keywords     = {{Minimal problems; RANSAC; Self-calibration; TDOA}},
  language     = {{eng}},
  pages        = {{4640--4644}},
  series       = {{ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}},
  title        = {{Fast and robust stratified self-calibration using time-difference-of-arrival measurements}},
  url          = {{http://dx.doi.org/10.1109/ICASSP39728.2021.9414309}},
  doi          = {{10.1109/ICASSP39728.2021.9414309}},
  volume       = {{2021-June}},
  year         = {{2021}},
}