A Controlled-Environment Quality Assessment of Android GNSS Raw Measurements

Gogoi, Neil; Minetto, Alex; Linty, Nicola; Dovis, Fabio

doi:10.3390/electronics8010005

Cited by 49 publications

(30 citation statements)

References 13 publications

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“…Looking at the Android documentation, we realize that not all devices are equivalent and that the quality of positioning depends largely on the manufacturer's choices. Thus, depending on the models, the results obtained can be different as illustrated in (Gogoi et al, 2018;Kalleev, Saburova, 2018;Dabove, Di Pietra, 2019). The most promising results were achieved with the Xiaomi MI 8, the first dual-frequency smartphone on the market released in 2018.…”

Section: Introductionmentioning

confidence: 99%

Development of a Low-Cost Centimetric GNSS Positioning Solution for Android Applications

Semler

Mangin²,

Moussaoui³

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. With the smartphone boom, positioning oneself on the Earth's surface has become something common. Everyone know how to uses their smartphone to get their location or finding their way. However, achieve centimetric accuracy on positioning still a topical issue that arouses considerable interest. Geodetic GNSS antennas are currently used for this field, but their price is incompatible with the mass market applications (autonomous cars, drones, machine automation, photogrammetry, etc.). In this paper, an approach to improve the Android smartphone positioning is presented using low-cost GNSS receiver. Requested by Syslor, a start-up working in buried networks, the society want to enhance its customer services. The purpose of this study is to present a method to reach centimetric localisation of smartphones for augmented reality and as-built 3D plans applications.

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Section: Introductionmentioning

confidence: 99%

Development of a Low-Cost Centimetric GNSS Positioning Solution for Android Applications

Semler

Mangin²,

Moussaoui³

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…This is due to the quality of the raw measurements, that are noisier than those obtainable with other mass-market receivers, such as the u-blox. The analysis of the signal is not the topic of this paper, but the same devices were analyzed in [23].…”

Section: Positioning Performances Considering Different Environmentsmentioning

confidence: 99%

GNSS Positioning Using Mobile Devices with the Android Operating System

Dabove

Pietra

Piras

2020

IJGI

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The access and the use of the global navigation satellite system (GNSS) pseudo-range and carrier-phase measurements mobile devices as smartphones and tablets with an Android operating system has transformed the concept of accurate positioning with mobile devices. In this work, the comparison of positioning performances obtained with a smartphone and an external mass-market GNSS receiver both in real-time and post-processing is made. Particular attention is also paid to accuracy and precision of positioning results, also analyzing the possibility of estimating the phase ambiguities as integer values (fixed positioning) that it is still challenging for mass-market devices. The precisions and accuracies obtained with the mass-market receiver were about 5 cm and 1 cm both for real-time and post-processing solutions, respectively, while those obtained with a smartphone were slightly worse (few meters in some cases) due to the noise of its measurements.

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“…As for the positioning performance under complex dynamic environments, Zhang et al adopted a time-differenced filtering to process the raw Global Positioning System (GPS) L1 measurements from a Nexus 9 tablet in the GNSS-degraded environment, and the resulting position trajectory fluctuated seriously and obvious discontinuities existed [2]. Clearly, due to low-cost single frequency GNSS chipsets and linearly polarized planar inverted F (PIF) antenna embedded in smartphones, the quality of the raw single frequency GNSS observations is usually poor [13,14]. The navigation performance is thus unsatisfactory especially in GNSS-degraded environments.…”

Section: Introductionmentioning

confidence: 99%

Characteristics Analysis of Raw Multi-GNSS Measurement from Xiaomi Mi 8 and Positioning Performance Improvement with L5/E5 Frequency in an Urban Environment

et al. 2020

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Achieving continuous and high-precision positioning services via smartphone under a Global Navigation Satellite System (GNSS)-degraded environment is urgently demanded by the mass market. In 2018, Xiaomi launched the world’s first dual-frequency GNSS smartphone, Xiaomi Mi 8. The newly added L5/E5 signals are more precise and less prone to distortions from multipath reflections. This paper discusses the characteristics of raw dual-frequency GNSS observations from Xiaomi Mi 8 in urban environments; they are characterized by high pseudorange noise and frequent signal interruption. The traditional dual-frequency ionosphere-free combination is not suitable for Xiaomi Mi 8 raw GNSS data processing, since the noise of the combined measurements is much larger than the influence of the ionospheric delay. Therefore, in order to reasonably utilize the high precision carrier phase observations, a time differenced positioning filter is presented in this paper to deliver continuous and smooth navigation results in urban environments. The filter first estimates the inter-epoch position variation (IEPV) with time differenced uncombined L1/E1 and L5/E5 carrier phase observations and constructs the state equation with IEPV to accurately describe the user’s movement. Secondly, the observation equations are formed with uncombined L1/E1 and L5/E5 pseudorange observations. Then, kinematic experiments in open-sky and GNSS-degraded environments are carried out, and the proposed filter is assessed in terms of the positioning accuracy and solution availability. The result in an open-sky environment shows that, assisted with L5/E5 observations, the root mean square (RMS) of the stand-alone horizontal and vertical positioning errors are about 1.22 m and 1.94 m, respectively, with a 97.8% navigation availability. Encouragingly, even in a GNSS-degraded environment, smooth navigation services with accuracies of 1.61 m and 2.16 m in the horizontal and vertical directions are obtained by using multi-GNSS and L5/E5 observations.

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A Controlled-Environment Quality Assessment of Android GNSS Raw Measurements

Cited by 49 publications

References 13 publications

Development of a Low-Cost Centimetric GNSS Positioning Solution for Android Applications

Development of a Low-Cost Centimetric GNSS Positioning Solution for Android Applications

GNSS Positioning Using Mobile Devices with the Android Operating System

Characteristics Analysis of Raw Multi-GNSS Measurement from Xiaomi Mi 8 and Positioning Performance Improvement with L5/E5 Frequency in an Urban Environment

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