Multiple Offsets Multilateration::  A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes

Luca Ferranti; Kalle Aström; Magnus Oskarsson; Jani Boutellier; Juho Kannala

doi:10.1109/ICASSP43922.2022.9746922

Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes

Luca Ferranti, Kalle Aström, Magnus Oskarsson, Jani Boutellier, Juho Kannala

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

Abstract

Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters as well as time offsets if the devices are unsynchronized. In this paper, we expand the previous state-of-the-art on positioning formulations by introducing Multiple Offsets Multilateration (MOM), a new mathematical framework to compute the receivers positions with pseudoranges from unsynchronized reference transmitters at known positions. This could be applied in several scenarios, for example structure from sound and positioning with LEO satellites. We mathematically describe MOM, determining how many receivers and transmitters are needed for the network to be solvable, a study on the number of possible distinct solutions is presented and stable solvers based on homotopy continuation are derived. The solvers are shown to be efficient and robust to noise both for synthetic and real audio data.

Original language	English
Title of host publication	2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	4958-4962
Number of pages	5
ISBN (Electronic)	9781665405409
DOIs	https://doi.org/10.1109/ICASSP43922.2022.9746922
Publication status	Published - 2022
Event	47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore Duration: 2022 May 23 → 2022 May 27

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2022-May
ISSN (Print)	1520-6149

Conference

Conference	47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/Territory	Singapore
City	Virtual, Online
Period	2022/05/23 → 2022/05/27

Bibliographical note

Funding Information:
This work was partially funded by the Academy of Finland project 327912 REPEAT and the Swedish strategic research project ELLIIT.The authors gratefully acknowledge Lund University Humanities Lab.

Publisher Copyright:
© 2022 IEEE

Subject classification (UKÄ)

Signal Processing

Free keywords

Homotopy Continuation
Minimal Problems
Multilateration
Sensor Networks Calibration

Access to Document

10.1109/ICASSP43922.2022.9746922

Cite this

Ferranti, L., Aström, K., Oskarsson, M., Boutellier, J., & Kannala, J. (2022). Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes. In 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings (pp. 4958-4962). (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2022-May). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP43922.2022.9746922

Ferranti, Luca ; Aström, Kalle ; Oskarsson, Magnus et al. / Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes. 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE - Institute of Electrical and Electronics Engineers Inc., 2022. pp. 4958-4962 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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abstract = "Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters as well as time offsets if the devices are unsynchronized. In this paper, we expand the previous state-of-the-art on positioning formulations by introducing Multiple Offsets Multilateration (MOM), a new mathematical framework to compute the receivers positions with pseudoranges from unsynchronized reference transmitters at known positions. This could be applied in several scenarios, for example structure from sound and positioning with LEO satellites. We mathematically describe MOM, determining how many receivers and transmitters are needed for the network to be solvable, a study on the number of possible distinct solutions is presented and stable solvers based on homotopy continuation are derived. The solvers are shown to be efficient and robust to noise both for synthetic and real audio data.",

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author = "Luca Ferranti and Kalle Astr{\"o}m and Magnus Oskarsson and Jani Boutellier and Juho Kannala",

note = "Funding Information: This work was partially funded by the Academy of Finland project 327912 REPEAT and the Swedish strategic research project ELLIIT.The authors gratefully acknowledge Lund University Humanities Lab. Publisher Copyright: {\textcopyright} 2022 IEEE; 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 ; Conference date: 23-05-2022 Through 27-05-2022",

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Ferranti, L, Aström, K , Oskarsson, M, Boutellier, J & Kannala, J 2022, Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes. in 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2022-May, IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 4958-4962, 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, Virtual, Online, Singapore, 2022/05/23. https://doi.org/10.1109/ICASSP43922.2022.9746922

Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes. / Ferranti, Luca; Aström, Kalle ; Oskarsson, Magnus et al.

2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE - Institute of Electrical and Electronics Engineers Inc., 2022. p. 4958-4962 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2022-May).

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

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T2 - 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022

AU - Ferranti, Luca

AU - Aström, Kalle

AU - Oskarsson, Magnus

AU - Boutellier, Jani

AU - Kannala, Juho

N1 - Funding Information: This work was partially funded by the Academy of Finland project 327912 REPEAT and the Swedish strategic research project ELLIIT.The authors gratefully acknowledge Lund University Humanities Lab. Publisher Copyright: © 2022 IEEE

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N2 - Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters as well as time offsets if the devices are unsynchronized. In this paper, we expand the previous state-of-the-art on positioning formulations by introducing Multiple Offsets Multilateration (MOM), a new mathematical framework to compute the receivers positions with pseudoranges from unsynchronized reference transmitters at known positions. This could be applied in several scenarios, for example structure from sound and positioning with LEO satellites. We mathematically describe MOM, determining how many receivers and transmitters are needed for the network to be solvable, a study on the number of possible distinct solutions is presented and stable solvers based on homotopy continuation are derived. The solvers are shown to be efficient and robust to noise both for synthetic and real audio data.

AB - Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters as well as time offsets if the devices are unsynchronized. In this paper, we expand the previous state-of-the-art on positioning formulations by introducing Multiple Offsets Multilateration (MOM), a new mathematical framework to compute the receivers positions with pseudoranges from unsynchronized reference transmitters at known positions. This could be applied in several scenarios, for example structure from sound and positioning with LEO satellites. We mathematically describe MOM, determining how many receivers and transmitters are needed for the network to be solvable, a study on the number of possible distinct solutions is presented and stable solvers based on homotopy continuation are derived. The solvers are shown to be efficient and robust to noise both for synthetic and real audio data.

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DO - 10.1109/ICASSP43922.2022.9746922

M3 - Paper in conference proceeding

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BT - 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

Y2 - 23 May 2022 through 27 May 2022

ER -

Ferranti L, Aström K , Oskarsson M, Boutellier J, Kannala J. Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes. In 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE - Institute of Electrical and Electronics Engineers Inc. 2022. p. 4958-4962. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP43922.2022.9746922