Enabling High Accuracy Dynamic Applications in Urban Environments Using PPP and RTK on Android Multi-Frequency and Multi-GNSS Smartphones

Fortunato, Marco; Critchley-Marrows, Joshua; Siutkowska, Malgorzata; Ivanovici, Maria; Benedetti, Elisa; Roberts, William

doi:10.1109/euronav.2019.8714140

Cited by 53 publications

(40 citation statements)

References 7 publications

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“…The NSL’s FLAMINGO (Nottingham Scientific Limited’s fulfilling enhanced location accuracy in the mass-market through Initial Galileo Services) Team [10,11] assessed the quality of the GNSS raw measurements from Xiaomi MI 8 smartphones in July 2018. They considered that the carrier phase was not affected by duty cycling, and the raw observations quality of L5/E5 frequency are better than L1/E1 frequency.…”

Section: Introductionmentioning

confidence: 99%

Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone

Chen

Gao

Liu

et al. 2019

Sensors

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The Global Navigation Satellite System (GNSS) positioning technology using smartphones can be applied to many aspects of mass life, and the world’s first dual-frequency GNSS smartphone Xiaomi MI 8 represents a new trend in the development of GNSS positioning technology with mobile phones. The main purpose of this work is to explore the best real-time positioning performance that can be achieved on a smartphone without reference stations. By analyzing the GNSS raw measurements, it is found that all the three mobile phones tested have the phenomenon that the differences between pseudorange observations and carrier phase observations are not fixed, thus a PPP (precise point positioning) method is modified accordingly. Using a Xiaomi MI 8 smartphone, the modified real-time PPP positioning strategy which estimates two clock biases of smartphone was applied. The results show that using multi-GNSS systems data can effectively improve positioning performance; the average horizontal and vertical RMS positioning error are 0.81 and 1.65 m respectively (using GPS, BDS, and Galileo data); and the time required for each time period positioning errors in N and E directions to be under 1 m is less than 30s.

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Section: Introductionmentioning

confidence: 99%

Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone

Chen

Gao

Liu

et al. 2019

Sensors

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“…The availability of GNSS measurements from such mass-market devices encourages researchers to extend the use of traditional algorithms that were originally developed for high-end receivers to include this new generation of GNSS devices, aiming mainly at increasing the positioning accuracy. Real-time kinematic (RTK) and Precise Point Positioning (PPP), for example, are widely used to exploit the benefits coming from the accessibility of the raw GNSS measurements [1][2][3][4]. 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.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Geophysical Applications with Android GNSS Raw Measurements

2019

Self Cite

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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.

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“…Furthermore, it has been shown that RTK may be available for smart phones and provide cm-level accuracy in the opensky conditions [16]. However, its performance can be degraded in urban environment, e.g., due to the cycle-slips phenomenon [17,18].…”

Section: Related Workmentioning

confidence: 99%

Modeling of Real Time Kinematics localization error for use in 5G networks

Hoffmann

Kryszkiewicz

Koudouridis

2020

J Wireless Com Network

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In 5G networks information about localization of a user equipment (UE) can be used not only for emergency calls or location-based services, but also for the network optimization applications, e.g., network management or dynamic spectrum access by using Radio Environment Maps (REM). However, some of these applications require much better localization accuracy than currently available in 4G systems. One promising localization method is Global Navigation Satellite System (GNSS)-based Real-Time Kinematics (RTK). While the signal received from satellites is the same as in traditional GNSS, a new reception method utilizing real-time data from a nearby reference station (e.g., 5G base station) results in cm-level positioning accuracy. The aim of this paper is to obtain a model of the RTK localization error for smartphone-grade GNSS antenna under open-sky conditions, that can be used in 5G network simulators. First, a tutorial-style overview of RTK positioning, and satellite orbits prediction is provided. Next, an RTK localization simulator is implemented utilizing GNSS satellites constellations. Results are investigated statistically to provide a simple, yet accurate RTK localization error framework, which is based on two Gauss-Markov process generators parametrized by visible satellites geometry, UE motion, and UE-satellite distance error variance.

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Enabling High Accuracy Dynamic Applications in Urban Environments Using PPP and RTK on Android Multi-Frequency and Multi-GNSS Smartphones

Cited by 53 publications

References 7 publications

Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone

Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone

Real-Time Geophysical Applications with Android GNSS Raw Measurements

Modeling of Real Time Kinematics localization error for use in 5G networks

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