Upgrade Methods for Stratified Sensor Network Self-Calibration
Larsson, M.; Flood, G.; Oskarsson, M.; Astrom, K. (2020). Upgrade Methods for Stratified Sensor Network Self-Calibration 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings, 2020-May,, 4851 - 4855. 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020. Barcelona, Spain: IEEE - Institute of Electrical and Electronics Engineers Inc.
Conference Proceeding/Paper
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Published
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English
Authors:
Larsson, M.
;
Flood, G.
;
Oskarsson, M.
;
Astrom, K.
Department:
Mathematics (Faculty of Engineering)
ELLIIT: the Linköping-Lund initiative on IT and mobile communication
eSSENCE: The e-Science Collaboration
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.
Keywords:
Calibration ;
Minimal Problems ;
RANSAC ;
Time-difference-of-arrival ;
Time-of-arrival
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