The Quality Analysis of GNSS Observations Tracked by Android Smart Devices and Positioning Performance Assessment

EGU21-334, updated on 28 Sep 2021 https://doi.org/10.5194/egusphere-egu21-334 EGU General Assembly 2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.

The quality analysis of GNSS observations tracked by Android smart devices and positioning performance assessment

Jacek Paziewski1, Marco Fortunato2, Augusto Mazzoni2, Robert Odolinski3, Guangcai Li4, Mathilde Debelle5, René Warnant5, and Xiaopeng Gong4 1Department of Geodesy, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland ([email protected]) 2Geodesy and Geomatics Division DICEA, Sapienza University of Rome, Rome, Italy 3National School of Surveying, University of Otago, Dunedin, New Zealand 4GNSS Research Center, Wuhan University, Wuhan, China 5Geomatics Unit, University of Liège, Liège, Belgium

This study assesses the quality of multi-constellation GNSS observations of selected Android smartphones namely Huawei P30, Huawei P20 and Huawei P Smart as well as Xiaomi Mi 8 and Xiaomi Mi 9. We investigate the properties of phase ambiguities to anticipate the feasibility of precise positioning with integer ambiguity fixing. The results reveal a significant drop of smartphone carrier-to-noise density ratio (C/N0) with respect to geodetic receivers and discernible differences among constellations and frequency bands. We show that the higher the elevation of the satellite, the larger discrepancy in C/N0 between the geodetic receivers and smartphones. We depict that an elevation dependence of the signal strength is not always the case for the smartphones. We discover that smartphone code pseudoranges are noisier by about one order of magnitude as compared to the geodetic receivers, and that the code signals on L5 and E5a outperform these on L1 and E1, respectively. It was shown that smartphone phase observations are contaminated by the effects that can destroy the integer property and time-constancy of the ambiguities. The long term drifts were detected for GPS L5, Galileo E1, E5a and BDS B1 phase observations of Huawei P30. To isolate the observational noise from low frequency effects we take advantage of time differencing using the variometric approach. These investigations highlight competitive phase noise characteristics for the Xiaomi Mi 8 when compared to the geodetic receivers. We also reveal poor phase signal quality for the Huawei P30 smartphones related to the unexpected long-term drifts of the phase signals. The observation quality assessment is supported with the evaluation of a positioning performance. We proved that it is feasible to obtain a precise solution in a smartphone to smartphone relative positioning mode with fixed ambiguities. Such results move us towards a collaborative precise positioning with smartphones.