A theoretical and empirical integrated method to select the optimal combined signals for geometry-free and geometry-based three-carrier ambiguity resolution

Zhao, Dongsheng, Roberts, Gethin Wyn, Lau, Lawrence, Hancock, Craig and Bai, Ruibin (2016) A theoretical and empirical integrated method to select the optimal combined signals for geometry-free and geometry-based three-carrier ambiguity resolution. Sensors, 16 (11). 1929/1-1929/19. ISSN 1424-8220

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Abstract

12 GPS Block IIF satellites, out of the current constellation, can transmit on three-frequency signals (L1, L2, L5). Taking advantages of these signals, Three-Carrier Ambiguity Resolution (TCAR) is expected to bring much benefit for ambiguity resolution. One of the research areas is to find the optimal combined signals for a better ambiguity resolution in geometry-free (GF) and geometry-based (GB) mode. However, the existing researches select the signals through either pure theoretical analysis or testing with simulated data, which might be biased as the real observation condition could be different from theoretical prediction or simulation. In this paper, we propose a theoretical and empirical integrated method, which first selects the possible optimal combined signals in theory and then refines these signals with real triple-frequency GPS data, observed at eleven baselines of different lengths. An interpolation technique is also adopted in order to show changes of the AR performance with the increase in baseline length. The results show that the AR success rate can be improved by 3% in GF mode and 8% in GB mode at certain intervals of the baseline length. Therefore, the TCAR can perform better by adopting the combined signals proposed in this paper when the baseline meets the length condition.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/828374
Keywords: GPS; ambiguity resolution; geometry-free; geometry-based; triple-frequency observations; real data
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Computer Science
University of Nottingham Ningbo China > Faculty of Science and Engineering > Division of Engineering
University of Nottingham, UK > Faculty of Engineering
Identification Number: 10.3390/s16111929
Depositing User: Eprints, Support
Date Deposited: 02 Nov 2016 10:29
Last Modified: 04 May 2020 18:20
URI: https://eprints.nottingham.ac.uk/id/eprint/38434

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