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Precise Positioning with Smartphones

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 32942

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Special Issue Editors


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Guest Editor
Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada
Interests: satellite-based navigation; inertial navigation; multi-sensor integration; precision GNSS; GPS; PPP
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
The Faculty of Geoengineering, Department of Geodesy, University of Warmia and Mazury in Olsztyn (UWM), Oczapowskiego 1, 10-719 Olsztyn, Poland
Interests: GNSS; precise positioning; high-rate GNSS data processing; integration of multi-constellation signals; modelling of the ionospheric delay with GNSS; displacement and deformation monitoring; structural monitoring with GNSS; smartphone GNSS positioning
Special Issues, Collections and Topics in MDPI journals
Software Engineer, Google Android Location Team, Mountain View, CA, USA
Interests: GNSS; GPS; sensor fusion; computing

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Guest Editor
Geodesy and Geomatics Division, DICEA, Sapienza University of Rome, Via Eudossiana 18, 00182 Rome, Italy
Interests: positioning and monitoring with GNSS; GNSS seismology; GNSS meteorology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few years, many smartphones have been equipped with Global Navigation Satellite System (GNSS) technology, allowing smartphone users to use their own devices for positioning purposes. After the release of the Android Nougat (version 7) operating systems, raw GNSS measurements (i.e., the pseudorange, carrier-phase, Doppler shift and carrier-to-noise density ratio (C/N0) observations) from smartphones and tablets became accessible, which opened the door to developing precise positioning capability in consumer devices. Since then, many studies have been conducted, as precise location information will lead to many new smartphone applications in the near future. While the progress has been encouraging, a number of limiting factors must be overcome in order to support real-world applications, including poor antenna quality, the difficulty of carrier-phase ambiguity resolution, and low availability and integrity in operational environments. Through this Special Issue, we invite contributions from academia and industry to discuss innovative ideas and algorithms and demonstrate testing results for precise positioning with Android smartphones. The topics of interest include, but are not limited to, the following:

  • The analysis and modeling of smartphone GNSS observations
  • Smartphone GNSS error estimation and mitigation
  • Functional and stochastic models for precise positioning with smartphones
  • Smartphone positioning with precise point positioning (PPP), real-team kinematic (RTK), machine learning (ML), and other advanced techniques
  • Carrier-phase ambiguity resolution with smartphone GNSS observations
  • The integrity monitoring of smartphone-based positioning
  • Smartphone antenna analysis and calibration
  • Smartphone GNSS and inertial sensor integration
  • Location-based services with precision GNSS smartphones
  • Applications of precision GNSS smartphones

Prof. Dr. Yang Gao 
Prof. Dr. Jacek Paziewski 
Dr. Michael Fu
Prof. Dr. Augusto Mazzoni
Guest Editor

Manuscript Submission Information

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Published Papers (10 papers)

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Research

19 pages, 5364 KiB  
Article
An Improved Ambiguity Resolution Algorithm for Smartphone RTK Positioning
by Yang Jiang, Yuting Gao, Wei Ding, Fei Liu and Yang Gao
Sensors 2023, 23(11), 5292; https://doi.org/10.3390/s23115292 - 2 Jun 2023
Cited by 5 | Viewed by 1415
Abstract
Ambiguity resolution based on smartphone GNSS measurements can enable various potential applications that currently remain difficult due to ambiguity biases, especially under kinematic conditions. This study proposes an improved ambiguity resolution algorithm, which uses the search-and-shrink procedure coupled with the methods of the [...] Read more.
Ambiguity resolution based on smartphone GNSS measurements can enable various potential applications that currently remain difficult due to ambiguity biases, especially under kinematic conditions. This study proposes an improved ambiguity resolution algorithm, which uses the search-and-shrink procedure coupled with the methods of the multi-epoch double-differenced residual test and the ambiguity majority tests for candidate vectors and ambiguities. By performing a static experiment with Xiaomi Mi 8, the AR efficiency of the proposed method is evaluated. Furthermore, a kinematic test with Google Pixel 5 verifies the effectiveness of the proposed method with improved positioning performance. In conclusion, centimeter-level smartphone positioning accuracy is achieved in both experiments, which is greatly improved compared with the float and traditional AR solutions. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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17 pages, 26428 KiB  
Article
A Comprehensive Analysis of Smartphone GNSS Range Errors in Realistic Environments
by Jiahuan Hu, Ding Yi and Sunil Bisnath
Sensors 2023, 23(3), 1631; https://doi.org/10.3390/s23031631 - 2 Feb 2023
Cited by 6 | Viewed by 2159
Abstract
Precise positioning using smartphones has been a topic of interest especially after Google decided to provide raw GNSS measurement through their Android platform. Currently, the greatest limitations in precise positioning with smartphone Global Navigation Satellite System (GNSS) sensors are the quality and availability [...] Read more.
Precise positioning using smartphones has been a topic of interest especially after Google decided to provide raw GNSS measurement through their Android platform. Currently, the greatest limitations in precise positioning with smartphone Global Navigation Satellite System (GNSS) sensors are the quality and availability of satellite-to-smartphone ranging measurements. Many papers have assessed the quality of GNSS pseudorange and carrier-phase measurements in various environments. In addition, there is growing research in the inclusion of a priori information to model signal blockage, multipath, etc. In this contribution, numerical estimation of actual range errors in smartphone GNSS precise positioning in realistic environments is performed using a geodetic receiver as a reference. The range errors are analyzed under various environments and by placing smartphones on car dashboards and roofs. The distribution of range errors and their correlation to prefit residuals is studied in detail. In addition, a comparison of range errors between different constellations is provided, aiming to provide insight into the quantitative understanding of measurement behavior. This information can be used to further improve measurement quality control, and optimize stochastic modeling and position estimation processes. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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18 pages, 5866 KiB  
Article
Precise Position Estimation Using Smartphone Raw GNSS Data Based on Two-Step Optimization
by Taro Suzuki
Sensors 2023, 23(3), 1205; https://doi.org/10.3390/s23031205 - 20 Jan 2023
Cited by 5 | Viewed by 3948
Abstract
This paper presents a high-precision positioning method using raw global navigation satellite system (GNSS) observations from smartphones in the Google smartphone decimeter challenge (GSDC). Compared to commercial GNSS receivers, smartphone GNSS observations are noisy owing to antenna limitations, making it difficult to apply [...] Read more.
This paper presents a high-precision positioning method using raw global navigation satellite system (GNSS) observations from smartphones in the Google smartphone decimeter challenge (GSDC). Compared to commercial GNSS receivers, smartphone GNSS observations are noisy owing to antenna limitations, making it difficult to apply conventional high-precision positioning methods. In addition, it is important to exclude outliers in GSDC because GSDC includes data in environments where GNSS is shielded, such as tunnels and elevated structures. Therefore, this study proposes a smartphone positioning method based on a two-step optimization method, using factor graph optimization (FGO). Here, the velocity and position optimization process are separated and the velocity is first estimated from Doppler observations. Then, the outliers of the velocity estimated by FGO are excluded, while the missing velocity is interpolated. In the next position-optimization step, the velocity estimated in the previous step is adopted as a loose state-to-state constraint and the position is estimated using the time-differenced carrier phase (TDCP), which is more accurate than Doppler, but less available. The final horizontal positioning accuracy was 1.229 m, which was the first place, thus demonstrating the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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24 pages, 14473 KiB  
Article
GNSS Observation Generation from Smartphone Android Location API: Performance of Existing Apps, Issues and Improvement
by Farzaneh Zangenehnejad, Yang Jiang and Yang Gao
Sensors 2023, 23(2), 777; https://doi.org/10.3390/s23020777 - 10 Jan 2023
Cited by 13 | Viewed by 4347
Abstract
Precise position information available from smartphones can play an important role in developing new location-based service (LBS) applications. Starting from 2016, and after the release of Nougat version (Version 7) by Google, developers have had access to the GNSS raw measurements through the [...] Read more.
Precise position information available from smartphones can play an important role in developing new location-based service (LBS) applications. Starting from 2016, and after the release of Nougat version (Version 7) by Google, developers have had access to the GNSS raw measurements through the new application programming interface (API), namely android.location (API level 24). However, the new API does not provide the typical GNSS observations directly (e.g., pseudorange, carrier-phase and Doppler observations) which have to be generated by the users themselves. Although several Apps have been developed for the GNSS observations generation, various data analyses indicate quality concerns, from biases to observation inconsistency in the generated GNSS observations output from those Apps. The quality concerns would subsequently affect GNSS data processing such as cycle slip detection, code smoothing and ultimately positioning performance. In this study, we first investigate algorithms for GNSS observations generation from the android.location API output. We then evaluate the performances of two widely used Apps (Geo++RINEX logger and GnssLogger Apps), as well as our newly developed one (namely UofC CSV2RINEX tool) which converts the CSV file to a Receiver INdependent Exchange (RINEX) file. Positioning performance analysis is also provided which indicates improved positioning accuracy using our newly developed tool. Future work finding out the potential reasons for the identified misbehavior in the generated GNSS observations is recommended; it will require a joint effort with the App developers. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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18 pages, 5146 KiB  
Article
Inherent Limitations of Smartphone GNSS Positioning and Effective Methods to Increase the Accuracy Utilizing Dual-Frequency Measurements
by Jeonghyeon Yun, Cheolsoon Lim and Byungwoon Park
Sensors 2022, 22(24), 9879; https://doi.org/10.3390/s22249879 - 15 Dec 2022
Cited by 6 | Viewed by 3179
Abstract
Xiaomi Mi8 with a Broadcom BCM47755 chip, an Android smartphone that supports multi-constellation (GPS, GLONASS, Galileo, BeiDou, and QZSS) and dual-frequency (L1/E1 and L5/E5), was launched in May 2018. Unlike previously released smartphones, it was technically expected to provide robust precise positioning with [...] Read more.
Xiaomi Mi8 with a Broadcom BCM47755 chip, an Android smartphone that supports multi-constellation (GPS, GLONASS, Galileo, BeiDou, and QZSS) and dual-frequency (L1/E1 and L5/E5), was launched in May 2018. Unlike previously released smartphones, it was technically expected to provide robust precise positioning with a fast ambiguity resolution, which led many researchers to be overly optimistic about the applicability of high-accuracy techniques such as real-time kinematic (RTK) systems and precise point positioning (PPP) of smartphones. The global navigation satellite system (GNSS) raw measurement quality of Android smartphones is, however, inherently far lower than that of general GNSS receivers due to their structure, which accordingly makes it difficult for them to be realized. Considering inherent limitations of smartphones such as low-quality antenna, frequent cycle slips, and the duty cycle, a practical strategy including L5 measurements, pseudo-range corrections for L5, and a weighting method is proposed in this paper. The results show that the proposed methods of L5 differential GNSS (DGNSS) and Doppler-based filtering can guarantee a positioning accuracy of 1.75 m horizontally and 4.56 m vertically in an Android device, which is comparable to the performance of commercial low-cost receivers. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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20 pages, 37992 KiB  
Article
Real-Time Loosely Coupled 3DMA GNSS/Doppler Measurements Integration Using a Graph Optimization and Its Performance Assessments in Urban Canyons of New York
by Hoi-Fung Ng, Li-Ta Hsu, Max Jwo Lem Lee, Junchi Feng, Tahereh Naeimi, Mahya Beheshti and John-Ross Rizzo
Sensors 2022, 22(17), 6533; https://doi.org/10.3390/s22176533 - 30 Aug 2022
Cited by 9 | Viewed by 1974
Abstract
Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad [...] Read more.
Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system’s recorded data in New York City. The real-time forward-processed FGO can provide a root-mean-square error (RMSE) of about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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24 pages, 1936 KiB  
Article
An Adaptive Algorithm for Multipath Mitigation in GNSS Positioning with Android Smartphones
by Lorenzo Benvenuto, Tiziano Cosso and Giorgio Delzanno
Sensors 2022, 22(15), 5790; https://doi.org/10.3390/s22155790 - 3 Aug 2022
Cited by 8 | Viewed by 2568
Abstract
We present a solution for improving the robustness of GNSS positioning with Android devices. The proposed method combines an acquisition phase performed in a dedicated Android app (thus working on the edge) and a processing phase, based on a modified version of the [...] Read more.
We present a solution for improving the robustness of GNSS positioning with Android devices. The proposed method combines an acquisition phase performed in a dedicated Android app (thus working on the edge) and a processing phase, based on a modified version of the open source library RTKLIB, performed on a dedicated server. The processing phase applies an improved version of the RTK library based on an adaptive algorithm for mitigating the multipath effect on satellite radio signals received by smartphone’s antennas. The algorithm is built on top of an extended version of the sigma-epsilon model in which weights associated to observables potentially affected by multipath errors are computed using logged data. In the paper, we will focus our attention on the architecture of the proposed solution and discuss preliminary experimental results obtained with the resulting system. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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14 pages, 2957 KiB  
Article
Optimizing the Use of RTKLIB for Smartphone-Based GNSS Measurements
by Tim Everett, Trey Taylor, Dong-Kyeong Lee and Dennis M. Akos
Sensors 2022, 22(10), 3825; https://doi.org/10.3390/s22103825 - 18 May 2022
Cited by 12 | Viewed by 4728
Abstract
The Google Smartphone Decimeter Challenge (GSDC) was a competition held in 2021, where data from a variety of instruments useful for determining a phone’s position (signals from GPS satellites, accelerometer readings, gyroscope readings, etc.) using Android smartphones were provided to be processed/assessed in [...] Read more.
The Google Smartphone Decimeter Challenge (GSDC) was a competition held in 2021, where data from a variety of instruments useful for determining a phone’s position (signals from GPS satellites, accelerometer readings, gyroscope readings, etc.) using Android smartphones were provided to be processed/assessed in regard to the most accurate determination of the longitude and latitude of user positions. One of the tools that can be utilized to process the GNSS measurements is RTKLIB. RTKLIB is an open-source GNSS processing software tool that can be used with the GNSS measurements, including code, carrier, and doppler measurements, to provide real-time kinematic (RTK), precise point positioning (PPP), and post-processed kinematic (PPK) solutions. In the GSDC, we focused on the PPK capabilities of RTKLIB, as the challenge only required post-processing of past data. Although PPK positioning is expected to provide sub-meter level accuracies, the lower quality of the Android measurements compared to geodetic receivers makes this performance difficult to achieve consistently. Another latent issue is that the original RTKLIB created by Tomoji Takasu is aimed at commercial GNSS receivers rather than smartphones. Therefore, the performance of the original RTKLIB for the GSDC is limited. Consequently, adjustments to both the code-base and the default settings are suggested. When implemented, these changes allowed RTKLIB processing to score 5th place, based on the performance submissions of the prior GSDC competition. Detailed information on what was changed, and the steps to replicate the final results, are presented in the paper. Moreover, the updated code-base, with all the implemented changes, is provided in the public repository. This paper outlines a procedure to optimize the use of RTKLIB for Android smartphone measurements, highlighting the changes needed given the low-quality measurements from the mobile phone platform (relative to the survey grade GNSS receiver), which can be used as a basis point for further optimization for future GSDC competitions. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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14 pages, 3051 KiB  
Article
Instantaneous Best Integer Equivariant Position Estimation Using Google Pixel 4 Smartphones for Single- and Dual-Frequency, Multi-GNSS Short-Baseline RTK
by Chien Zheng Yong, Ken Harima, Eldar Rubinov, Simon McClusky and Robert Odolinski
Sensors 2022, 22(10), 3772; https://doi.org/10.3390/s22103772 - 16 May 2022
Cited by 7 | Viewed by 2580
Abstract
High-precision global navigation satellite system (GNSS) positioning and navigation can be achieved with carrier-phase ambiguity resolution when the integer least squares (ILS) success rate (SR) is high. The users typically prefer the float solution under the scenario of having a low SR, and [...] Read more.
High-precision global navigation satellite system (GNSS) positioning and navigation can be achieved with carrier-phase ambiguity resolution when the integer least squares (ILS) success rate (SR) is high. The users typically prefer the float solution under the scenario of having a low SR, and the ILS solution when the SR is high. The best integer equivariant (BIE) estimator is an alternative solution since it minimizes the mean squared errors (MSEs); hence, it will always be superior to both its float and ILS counterparts. There has been a recent development of GNSSs consisting of the Global Positioning System (GPS), Galileo, Quasi-Zenith Satellite System (QZSS), and the BeiDou Navigation Satellite System (BDS), which has made precise positioning with Android smartphones possible. Since smartphone tracking of GNSS signals is generally of poorer quality than with geodetic grade receivers and antennas, the ILS SR is typically less than one, resulting in the BIE estimator being the preferred carrier phase ambiguity resolution option. Therefore, in this contribution, we compare, for the first time, the BIE estimator to the ILS and float contenders while using GNSS data collected by Google Pixel 4 (GP4) smartphones for short-baseline real-time kinematic (RTK) positioning. It is demonstrated that the BIE estimator will always give a better RTK positioning performance than that of the ILS and float solutions while using both single- and dual-frequency smartphone GNSS observations. Lastly, with the same smartphone data, we show that BIE will always be superior to the float and ILS solutions in terms of the MSEs, regardless of whether the SR is at high, medium, or low levels. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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14 pages, 6533 KiB  
Article
A Combined Elevation Angle and C/N0 Weighting Method for GNSS PPP on Xiaomi MI8 Smartphones
by Yanjie Li, Changsheng Cai and Zhenyu Xu
Sensors 2022, 22(7), 2804; https://doi.org/10.3390/s22072804 - 6 Apr 2022
Cited by 8 | Viewed by 3130
Abstract
Traditionally, an elevation-angle-dependent weighting method is usually used for Global Navigation Satellite System (GNSS) positioning with a geodetic receiver. As smartphones adopt linearly polarized antenna and low-cost GNSS chips, different GNSS observation properties are exhibited. As a result, a carrier-to-noise ratio (C/N0)-dependent weighting [...] Read more.
Traditionally, an elevation-angle-dependent weighting method is usually used for Global Navigation Satellite System (GNSS) positioning with a geodetic receiver. As smartphones adopt linearly polarized antenna and low-cost GNSS chips, different GNSS observation properties are exhibited. As a result, a carrier-to-noise ratio (C/N0)-dependent weighting method is mostly used for smartphone-based GNSS positioning. However, the C/N0 is subject to the effects of the observation environment, resulting in an unstable observation weight. In this study, we propose a combined elevation angle and C/N0 weighting method for smartphone-based GNSS precise point positioning (PPP) by normalizing the C/N0-derived variances to the scale of the elevation-angle-derived variances. The proposed weighting method is validated in two kinematic PPP tests with different satellite visibility conditions. Compared with the elevation-angle-only and C/N0-only weighting methods, the combined weighting method can effectively enhance the smartphone-based PPP accuracy in a three-dimensional position by 22.7% and 24.2% in an open-sky area, and by 52.0% and 26.0% in a constrained visibility area, respectively. Full article
(This article belongs to the Special Issue Precise Positioning with Smartphones)
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