Observation Quality Assessment and Performance of GNSS Standalone Positioning with Code Pseudoranges of Dual-Frequency Android Smartphones

Robustelli, Umberto; Paziewski, Jacek; Pugliano, Giovanni

doi:10.3390/s21062125

Cited by 40 publications

(28 citation statements)

References 44 publications

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“…Previous studies have found that the data quality of GPS and Galileo L5/E5 frequency is better than L1/E1 [ 22 , 23 , 24 ], and the use of L1/E1 and L5/E5 dual-frequency data can effectively weaken ionospheric delay. However, due to the fact that the number of dual-frequency data obtained by the smartphone is small, the utilization rate of the dual-frequency data is low.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Smartphone Positioning and Accuracy Analysis Based on Real-Time Regional Ionospheric Correction Model

Liu

Gao

Peng

et al. 2021

Sensors

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As one of the main errors that affects Global Navigation Satellite System (GNSS) positioning accuracy, ionospheric delay also affects the improvement of smartphone positioning accuracy. The current ionospheric error correction model used in smartphones has a certain time delay and low accuracy, which is difficult to meet the needs of real-time positioning of smartphones. This article proposes a method to use the real-time regional ionospheric model retrieved from the regional Continuously Operating Reference Stations (CORS) observation data to correct the GNSS positioning error of the smartphone. To verify the accuracy of the model, using the posterior grid as the standard, the electron content error of the regional ionospheric model is less than 5 Total Electron Content Unit (TECU), which is about 50% higher than the Klobuchar model, and to further evaluate the impact of the regional ionosphere model on the real-time positioning accuracy of smartphones, carrier-smoothing pseudorange and single-frequency Precise Point Positioning (PPP) tests were carried out. The results show that the real-time regional ionospheric model can significantly improve the positioning accuracy of smartphones, especially in the elevation direction. Compared with the Klobuchar model, the improvement effect is more than 34%, and the real-time regional ionospheric model also shortens the convergence time of the elevation direction to 1 min. (The convergence condition is that the range of continuous 20 s is less than 0.5 m).

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Section: Conclusion and Discussionmentioning

confidence: 99%

Smartphone Positioning and Accuracy Analysis Based on Real-Time Regional Ionospheric Correction Model

Liu

Gao

Peng

et al. 2021

Sensors

View full text Add to dashboard Cite

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“…They also investigated the performance of single point positioning using the Galileo E5a pseudorange observations compared with those of the E1 signal. Robustelli et al (2021) then assessed the quality of the smartphone observations. The results indicated a low C/N 0 dependence on satellite elevation and a clear azimuthal asymmetry of signal gain.…”

Section: Absolute Positioningmentioning

confidence: 99%

“…also suggested a C/ N 0 weighting model instead of an elevation-dependent weighting model. Employing the C/N 0 weighting model instead of an elevation-dependent weighting model has been also reported byBanville et al (2019),Liu et al (2019),Paziewski et al (2019) andRobustelli et al (2021).…”

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confidence: 97%

GNSS smartphones positioning: advances, challenges, opportunities, and future perspectives

2021

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Starting from 2016, the raw Global Navigation Satellite System (GNSS) measurements can be extracted from the Android Nougat (or later) operating systems. Since then, GNSS smartphone positioning has been given much attention. A high number of related publications indicates the importance of the research in this field, as it has been doing in recent years. Due to the cost-effectiveness of the GNSS smartphones, they can be employed in a wide variety of applications such as cadastral surveys, mapping surveying applications, vehicle and pedestrian navigation and etc. However, there are still some challenges regarding the noisy smartphone GNSS observations, the environment effect and smartphone holding modes and the algorithm development part which restrict the users to achieve high-precision smartphone positioning. In this review paper, we overview the research works carried out in this field with a focus on the following aspects: first, to provide a review of fundamental work on raw smartphone observations and quality assessment of GNSS observations from major smart devices including Google Pixel 4, Google Pixel 5, Xiaomi Mi 8 and Samsung Ultra S20 in terms of their signal strengths and carrier-phase continuities, second, to describe the current state of smartphone positioning research field until most recently in 2021 and, last, to summarize major challenges and opportunities in this filed. Finally, the paper is concluded with some remarks as well as future research perspectives.

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“…Nowadays, the global positioning system (GPS), in a coded solution, is the primary method of position determination in modern air (Lachapelle et al., 1996; Ochieng et al., 2003; Brodin et al., 2005; Krasuski et al., 2020; Krasuski and Savchuk, 2020), land (Ojeda and Borenstein, 2007; MacLean, 2009; Naranjo et al., 2009; Zandbergen and Barbeau, 2011; Sun et al., 2017; Merry and Bettinger, 2019; Elhajj and Ochieng, 2020; Robustelli et al., 2021) and marine (Grant et al., 2009; Han et al., 2016; Ramesh et al., 2016; Bhatti and Humphreys, 2017; Glomsvoll and Bonenberg, 2017) navigation. Its use depends primarily on the positioning accuracy, which has been constantly changing over the last years, hence GPS applications depend on the current positioning accuracy of that system (Rudnicki and Specht, 2016; Specht, 2019). For this reason, it is important to determine the current GPS accuracy because it is decisive for the possibilities of using the system in various navigation applications.…”

Section: Introductionmentioning

confidence: 99%

Consistency analysis of global positioning system position errors with typical statistical distributions

Specht

2021

J. Navigation

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Research into statistical distributions of φ, λ and two-dimensional (2D) position errors of the global positioning system (GPS) enables the evaluation of its accuracy. Based on this, the navigation applications in which the positioning system can be used are determined. However, studies of GPS accuracy indicate that the empirical φ and λ errors deviate from the typical normal distribution, significantly affecting the statistical distribution of 2D position errors. Therefore, determining the actual statistical distributions of position errors (1D and 2D) is decisive for the precision of calculating the actual accuracy of the GPS system. In this paper, based on two measurement sessions (900,000 and 237,000 fixes), the distributions of GPS position error statistics in both 1D and 2D space are analysed. Statistical distribution measures are determined using statistical tests, the hypothesis on the normal distribution of φ and λ errors is verified, and the consistency of GPS position errors with commonly used statistical distributions is assessed together with finding the best fit. Research has shown that φ and λ errors for the GPS system are normally distributed. It is proven that φ and λ errors are more concentrated around the central value than in a typical normal distribution (positive kurtosis) with a low value of asymmetry. Moreover, φ errors are clearly more concentrated than λ errors. This results in larger standard deviation values for φ errors than λ errors. The differences in both values were 25–39%. Regarding the 2D position error, it should be noted that the value of twice the distance root mean square (2DRMS) is about 10–14% greater than the value of R95. In addition, studies show that statistical distributions such as beta, gamma, lognormal and Weibull are the best fit for 2D position errors in the GPS system.

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Observation Quality Assessment and Performance of GNSS Standalone Positioning with Code Pseudoranges of Dual-Frequency Android Smartphones

Cited by 40 publications

References 44 publications

Smartphone Positioning and Accuracy Analysis Based on Real-Time Regional Ionospheric Correction Model

Smartphone Positioning and Accuracy Analysis Based on Real-Time Regional Ionospheric Correction Model

GNSS smartphones positioning: advances, challenges, opportunities, and future perspectives

Consistency analysis of global positioning system position errors with typical statistical distributions

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