Self-Calibration for the Time-of-Arrival Positioning
| Autor: | Norbert Scherer-Negenborn, Michael Arens, Juri Sidorenko, Urs Hugentobler, Volker Schatz, Dimitri Bulatov |
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| Přispěvatelé: | Publica |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Calibration (statistics) Computer science time-of-arrival (TOA) 05 social sciences General Engineering 050801 communication & media studies 020206 networking & telecommunications 02 engineering and technology System of linear equations dimension lifting ddc Overdetermined system Maxima and minima 0508 media and communications Time of arrival Dimension (vector space) 0202 electrical engineering electronic engineering information engineering self-calibration General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Self calibration Algorithm lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 8, Pp 65726-65733 (2020) |
| Popis: | Self-calibration of time-of-arrival positioning systems is made difficult by the non-linearity of the relevant set of equations. This work applies dimension lifting to this problem. The objective function is extended by an additional dimension to allow the dynamics of the optimization to avoid local minima. Next to the usual numerical optimization, a partially analytical method is suggested, which makes the system of equations overdetermined proportionally to the number of measurements. Results with the lifted objective function are compared to those with the unmodified objective function. For evaluation purposes, the fractions of convergence to local minima are determined, for both synthetic data with random geometrical constellations and real measurements with a reasonable constellation of base stations. It is shown that the lifted objective function provides improved convergence in all cases, often significantly so. |
| Databáze: | OpenAIRE |
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