Quality analysis of multi-GNSS raw observations and a velocity-aided positioning approach based on smartphones

Liu, Wanke; Shi, Xiang; Zhu, Feng; Tao, Xianlu; Wang, Fuhong

doi:10.1016/j.asr.2019.01.004

Cited by 105 publications

(74 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The results reveal that the C/N0 of smartphone measurements is about 9.4 dB-Hz lower with respect to the Javad receiver. These results are in line with the conclusions drawn by Zhang et al (2018a), Gill et al (2017) and Liu et al (2019) who showed that C/N0 of raw smartphone measurements are in general 7.5-10 dB-Hz lower comparing to the high-grade hardware. Figure 4 presents C/N0 values with respect to the satellite elevation angle.…”

Section: Satellite Signal Power Analysissupporting

confidence: 92%

See 1 more Smart Citation

Signal characterization and assessment of code GNSS positioning with low-power consumption smartphones

2019

View full text Add to dashboard Cite

It has been acknowledged that smartphone GNSS observations suffer not only from high measurement noise and multipath but also from anomalies such as duty cycling and gradual accumulation of phase errors. These phenomena importantly constrain the application of smartphone phase measurement to high-precision techniques such as RTK or PPP. Hence, we aim at a comprehensive characterization of smartphone signal quality, including carrier-to-noise density ratio, measurement noise and anomalies present in observables with the focus on the impact of duty-cycling mode. The analysis confirms the abnormal properties of smartphone measurements related to the divergence between code and phase data and poor quality of the latter. To address these limitations, the second objective is to assess the smartphone medium-to long-range code-based relative positioning. This task includes the validation of the weighting scheme suited for handling the low quality of smartphone observations. The results show that it is feasible to use a sparse countrywide GNSS network as reference stations for codebased relative positioning. Even with the baselines over 100 km, we can significantly enhance the positioning with respect to a stand-alone solution and reach the submeter level of horizontal coordinate accuracy. We have also noticed a discernible benefit from the C/N0-dependent weighting scheme, which is superior to the satellite elevation one.

show abstract

Section: Satellite Signal Power Analysissupporting

confidence: 92%

“…Liu et al (2018) reported improvement of the performance of closerange relative positioning taking advantage of pseudorange smoothing. The pedestrian navigation algorithm that considers the duty cycling was proposed in Liu et al (2019). Nonetheless, the results are still not sufficiently conclusive.…”

Section: Introductionmentioning

confidence: 99%

Signal characterization and assessment of code GNSS positioning with low-power consumption smartphones

2019

View full text Add to dashboard Cite

show abstract

“…The skyplots analysis confirms the independence of the C/No values from the azimuth for both the receivers ( Figure 6). The results are in line with published research in this field [5,7,8]. Due to the short acquisition time-typical of GNSS applications for smartphones, no further multipath analysis could be carried out.…”

Section: Periodic Dynamic Scenariosupporting

confidence: 89%

“…However, high accuracy is prevented by the quality of GNSS measurements obtainable from Android smartphones, due especially to the characteristics of the GNSS antenna: shared with other communication systems (WiFi, Bluetooth, etc. ), low cost, and linearly polarized [5,6]. The research carried out so far has highlighted the low resistance to interference, cycle slip, and multipath effects, as well as a marked gain in the SNR with respect the geodetic class receivers [7].…”

Section: Introductionmentioning

confidence: 99%

“…The research carried out so far has highlighted the low resistance to interference, cycle slip, and multipath effects, as well as a marked gain in the SNR with respect the geodetic class receivers [7]. Researchers are also focusing their attention on the development of new positioning algorithms based on the integration of different GNSS measurements such as pseudorange and doppler and/or carrier-phase [5,8], or on the combination of GNSS and external information to overcome the low accuracy achievable with GNSS observables from Android devices.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Real-Time Geophysical Applications with Android GNSS Raw Measurements

2019

View full text Add to dashboard Cite

The number of Android devices enabling access to raw GNSS (Global Navigation Satellite System) measurements is rapidly increasing, thanks to the dedicated Google APIs. In this study, the Xiaomi Mi8, the first GNSS dual-frequency smartphone embedded with the Broadcom BCM47755 GNSS chipset, was employed by leveraging the features of L5/E5a observations in addition to the traditional L1/E1 observations. The aim of this paper is to present two different smartphone applications in Geoscience, both based on the variometric approach and able to work in real time. In particular, tests using both VADASE (Variometric Approach for Displacement Analysis Stand-alone Engine) to retrieve the 3D velocity of a stand-alone receiver in real-time, and VARION (Variometric Approach for Real-Time Ionosphere Observations) algorithms, able to reconstruct real-time sTEC (slant total electron content) variations, were carried out. The results demonstrate the contribution that mass-market devices can offer to the geosciences. In detail, the noise level obtained with VADASE in a static scenario—few mm/s for the horizontal components and around 1 cm/s for the vertical component—underlines the possibility, confirmed from kinematic tests, of detecting fast movements such as periodic oscillations caused by earthquakes. VARION results indicate that the noise level can be brought back to that of geodetic receivers, making the Xiaomi Mi8 suitable for real-time ionosphere monitoring.

show abstract

Algorithm and Application of the Iterative Running Mean Filter on the Pseudo-Range Differential Positioning Based on the Smartphone GNSS Observations

Yan

Chen

Pan

2022

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

Quality analysis of multi-GNSS raw observations and a velocity-aided positioning approach based on smartphones

Cited by 105 publications

References 14 publications

Signal characterization and assessment of code GNSS positioning with low-power consumption smartphones

Signal characterization and assessment of code GNSS positioning with low-power consumption smartphones

Real-Time Geophysical Applications with Android GNSS Raw Measurements

Algorithm and Application of the Iterative Running Mean Filter on the Pseudo-Range Differential Positioning Based on the Smartphone GNSS Observations

Contact Info

Product

Resources

About