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Optimal Trilateration Is an Eigenvalue Problem

Larsson, Martin LU ; Larsson, Viktor LU ; Astrom, Kalle LU and Oskarsson, Magnus LU (2019) 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 2019-May. p.5586-5590
Abstract

The problem of estimating receiver or sender node positions from measured receiver-sender distances is a key issue in different applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using UWB or using round-trip-time measurements between mobile phones and WiFi-units. In this paper we address the problem of optimally estimating a receiver position given a number of distance measurements to known sender positions, so called trilateration. We show that this problem can be rephrased as an eigenvalue problem. We also address different error models and the multilateration setting where an additional offset is also unknown, and show that these problems can be modeled using the same... (More)

The problem of estimating receiver or sender node positions from measured receiver-sender distances is a key issue in different applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using UWB or using round-trip-time measurements between mobile phones and WiFi-units. In this paper we address the problem of optimally estimating a receiver position given a number of distance measurements to known sender positions, so called trilateration. We show that this problem can be rephrased as an eigenvalue problem. We also address different error models and the multilateration setting where an additional offset is also unknown, and show that these problems can be modeled using the same framework.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Calibration, Multilateration, Optimal estimation, Trilateration
host publication
2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
volume
2019-May
article number
8683355
pages
5 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
conference location
Brighton, United Kingdom
conference dates
2019-05-12 - 2019-05-17
external identifiers
  • scopus:85068976138
ISBN
9781479981311
DOI
10.1109/ICASSP.2019.8683355
language
English
LU publication?
yes
id
bbb51fb3-f3aa-4b07-bb1c-709ff38c946e
date added to LUP
2019-07-23 17:10:59
date last changed
2020-01-13 02:15:06
@inproceedings{bbb51fb3-f3aa-4b07-bb1c-709ff38c946e,
  abstract     = {<p>The problem of estimating receiver or sender node positions from measured receiver-sender distances is a key issue in different applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using UWB or using round-trip-time measurements between mobile phones and WiFi-units. In this paper we address the problem of optimally estimating a receiver position given a number of distance measurements to known sender positions, so called trilateration. We show that this problem can be rephrased as an eigenvalue problem. We also address different error models and the multilateration setting where an additional offset is also unknown, and show that these problems can be modeled using the same framework.</p>},
  author       = {Larsson, Martin and Larsson, Viktor and Astrom, Kalle and Oskarsson, Magnus},
  booktitle    = {2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings},
  isbn         = {9781479981311},
  language     = {eng},
  pages        = {5586--5590},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Optimal Trilateration Is an Eigenvalue Problem},
  url          = {http://dx.doi.org/10.1109/ICASSP.2019.8683355},
  doi          = {10.1109/ICASSP.2019.8683355},
  volume       = {2019-May},
  year         = {2019},
}