Multiple Offsets Multilateration: : A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes
(2022) 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 2022-May. p.4958-4962- 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,... (More)
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
- Ferranti, Luca LU ; Aström, Kalle LU ; Oskarsson, Magnus LU ; Boutellier, Jani and Kannala, Juho
- organization
-
- LTH Profile Area: AI and Digitalization
- Stroke Imaging Research group (research group)
- Mathematics (Faculty of Engineering)
- ELLIIT: the Linköping-Lund initiative on IT and mobile communication
- eSSENCE: The e-Science Collaboration
- Mathematical Imaging Group (research group)
- LTH Profile Area: Engineering Health
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Homotopy Continuation, Minimal Problems, Multilateration, Sensor Networks Calibration
- host publication
- 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
- series title
- ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
- volume
- 2022-May
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
- conference location
- Virtual, Online, Singapore
- conference dates
- 2022-05-23 - 2022-05-27
- external identifiers
-
- scopus:85131248711
- ISSN
- 1520-6149
- ISBN
- 9781665405409
- DOI
- 10.1109/ICASSP43922.2022.9746922
- language
- English
- LU publication?
- yes
- additional info
- 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
- id
- 7c76a4a4-ac24-4ec2-a04f-3249554aa9a6
- date added to LUP
- 2022-12-29 13:33:08
- date last changed
- 2023-11-21 15:00:34
@inproceedings{7c76a4a4-ac24-4ec2-a04f-3249554aa9a6, abstract = {{<p>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.</p>}}, author = {{Ferranti, Luca and Aström, Kalle and Oskarsson, Magnus and Boutellier, Jani and Kannala, Juho}}, booktitle = {{2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings}}, isbn = {{9781665405409}}, issn = {{1520-6149}}, keywords = {{Homotopy Continuation; Minimal Problems; Multilateration; Sensor Networks Calibration}}, language = {{eng}}, pages = {{4958--4962}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}}, title = {{Multiple Offsets Multilateration: : A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes}}, url = {{http://dx.doi.org/10.1109/ICASSP43922.2022.9746922}}, doi = {{10.1109/ICASSP43922.2022.9746922}}, volume = {{2022-May}}, year = {{2022}}, }