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Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 15910

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Special Issue Editor

Dr. Umberto Robustelli

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Guest Editor

Department of Engineering, Parthenope University of Naples, 80133 Naples, Italy
Interests: geomatics; radio navigation signal; GNSS; remote sensing

Special Issue Information

Dear Colleagues,

As claimed in a European Union Agency for the Space Programme report, smartphones are now dominating the installed base of devices equipped with GNSS (Global Navigation Satellite System) chipsets. This has encouraged hardware and software manufacturers to equip the new-generation Android devices with high-performance GNSS chips capable of tracking dual-frequency multiconstellation data.

This topic is of such interest to the scientific community that the IAG has established the ”Reliability of Low-cost & Android GNSS in navigation and geosciences” working group.

The aim of the present Special Issue is to foster advances in smartphone-derived GNSS measurements for a wide range of practical applications and research studies. We encourage the submission of both theoretical and applied research results focused on various aspects, including but not limited to:

The characterization of smartphone-derived GNSS measurements’ quality;
The multipath mitigation of smartphone-derived GNSS measurements;
The identification and investigation of the anomalies present in smartphone observables;
The development of novel processing algorithms addressing smartphone GNSS observables characteristics;
The development of new applications based on GNSS smartphone signals.

Dr. Umberto Robustelli
Guest Editor

Manuscript Submission Information

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Keywords

GNSS
smartphone
absolute positioning
GNSS noise assessment
Android
Galileo
GPS

Published Papers (7 papers)

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Research

18 pages, 15145 KiB

Open AccessArticle

BDS/GPS/Galileo Precise Point Positioning Performance Analysis of Android Smartphones Based on Real-Time Stream Data

by Mengyuan Li, Guanwen Huang, Le Wang and Wei Xie

Remote Sens. 2023, 15(12), 2983; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15122983 - 08 Jun 2023

Cited by 3 | Viewed by 1329

Abstract

Smartphones with the Android operating system can acquire Global Navigation Satellite System (GNSS) raw pseudorange and carrier phase observations, which can provide a new way for the general public to obtain precise position information. However, only postprocessing precise orbit and clock offset products in some older smart devices are applied in current studies. The performances of precise point positioning (PPP) with the smartphone using real-time products and newly smartphones are still unrevealed, which is more valuable for real-time applications. This study investigates the observation data quality and multi-GNSS real-time PPP performance using recent smartphones. Firstly, the observed carrier-to-noise density ratio (C/N0), number of satellites and position dilution of precision (PDOP) of GNSS observations are evaluated. The results demonstrate that the C/N0 received by Huawei Mate40 is better than that of the Huawei P40 for GPS, BDS, QZSS and Galileo systems, while the GLONASS is poorer, and the PDOP of the Huawei P40 is slightly better than that of Mate40. Additionally, a comprehensive analysis of real-time precise orbit and clock offset products performance is conducted. The experiment result expresses that the orbit and clock offset performance of GPS and Galileo is better than that of BDS-3 and GLONASS, and BDS-2 is the worst. Finally, single- and dual-frequency multi-GNSS combined PPP experiments using observations received from smartphones and real-time products are conducted; the results indicate that the real-time static PPP using a smartphone can achieve decimeter-level positioning accuracy, and kinematic PPP can achieve meter-level positioning accuracy after convergence. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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17 pages, 4992 KiB

Open AccessArticle

Transfer Learning Approach for Indoor Localization with Small Datasets

by Jeonghyeon Yoon, Jisoo Oh and Seungku Kim

Remote Sens. 2023, 15(8), 2122; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15082122 - 17 Apr 2023

Cited by 1 | Viewed by 1029

Abstract

Indoor pedestrian localization has been the subject of a great deal of recent research. Various studies have employed pedestrian dead reckoning, which determines pedestrian positions by transforming data collected through sensors into pedestrian gait information. Although several studies have recently applied deep learning to moving object distance estimations using naturally collected everyday life data, this data collection approach requires a long time, resulting in a lack of data for specific labels or a significant data imbalance problem for specific labels. In this study, to compensate for the problems of the existing PDR, a method based on transfer learning and data augmentation is proposed for estimating moving object distances for pedestrians. Consistent high-performance moving object distance estimation is achieved using only a small training dataset, and the problem of the concentration of training data only on labels within a certain range is solved using window warping and scaling methods. The training dataset consists of the three-axes values of the accelerometer sensor and the pedestrian’s movement speed calculated based on GPS coordinates. All data and GPS coordinates are collected through the smartphone. A performance evaluation of the proposed moving pedestrian distance estimation system shows a high distance error performance of 3.59 m with only approximately 17% training data compared to other moving object distance estimation techniques. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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24 pages, 16752 KiB

Open AccessArticle

Exploiting the Sensitivity of Dual-Frequency Smartphones and GNSS Geodetic Receivers for Jammer Localization

by Polona Pavlovčič-Prešeren, Franc Dimc and Matej Bažec

Remote Sens. 2023, 15(4), 1157; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15041157 - 20 Feb 2023

Cited by 2 | Viewed by 1688

Abstract

Smartphones now dominate the Global Navigation Satellite System (GNSS) devices capable of collecting raw data. However, they also offer valuable research opportunities in intentional jamming, which has become a serious threat to the GNSS. Smartphones have the potential to locate jammers, but their robustness and sensitivity range need to be investigated first. In this study, the response of smartphones with dual-frequency, multi-constellation reception capability, namely, a Xiaomi Mi8, a Xiaomi 11T, a Samsung Galaxy S20, and a Huawei P40, to various single- and multi-frequency jammers is investigated. The two-day jamming experiments were conducted in a remote area with minimal impact on users, using these smartphones and two Leica GS18 and two Leica GS15 geodetic receivers, which were placed statically at the side of a road and in a line, approximately 10 m apart. A vehicle with jammers installed passed them several times at a constant speed. In one scenario, a person carrying the jammer was constantly tracked using a tacheometer to determine the exact distance to the receivers for each time stamp. The aim was, first, to determine the effects of the various jammers on the smartphones’ positioning capabilities and to compare their response in terms of the speed and quality of repositioning with professional geodetic receivers. Second, a method was developed to determine the position of the interference source by varying the signal loss threshold and the recovery time on the smartphone and the decaying carrier-to-noise ratio (CNR). The results indicate that GNSS observations from smartphones have an advantage over geodetic receivers in terms of localizing jammers because they do not lose the signal near the source of the jamming, but they are characterized by sudden drops in the CNR. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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20 pages, 11794 KiB

Open AccessArticle

A Robust Adaptive Filtering Algorithm for GNSS Single-Frequency RTK of Smartphone

by Yuxing Li, Jinzhong Mi, Yantian Xu, Bo Li, Dingxuan Jiang and Weifeng Liu

Remote Sens. 2022, 14(24), 6388; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14246388 - 17 Dec 2022

Cited by 7 | Viewed by 1697

Abstract

In this paper, a single-frequency real-time kinematic positioning (RTK) robust adaptive Kalman filtering algorithm is proposed in order to realize real-time dynamic high-precision positioning of smartphone global navigation satellite systems (GNSSs). A robust model is established by using the quartile method to dynamically determine the threshold value and eliminate the gross error of observation. The Institute of Geodesy and Geophysics Ⅲ (IGG Ⅲ) weight function is used to construct the position and speed classification adaptive factors to weaken the impact of state mutation errors. Based on the analysis of the measured data of Xiaomi 8 and Huawei P40 smartphones, simulated dynamic tests show that the overall accuracy of the Xiaomi 8 is improved by more than 85% with the proposed robust RTK algorithm, and the overall positioning error is less than 0.5 m in both open and sheltered environments. The overall accuracy of the Huawei P40 is improved by more than 25%. Furthermore, the overall positioning accuracy is better than 0.3 m in open environments, and about 0.8 m in blocked situations. Dynamic experiments show that the use of the robust adaptive RTK algorithm improves the full-time solution planar positioning accuracy of the Xiaomi 8 by more than 15%. In addition, the planar positioning accuracy under open and occluded conditions is 0.8 m and 1.5 m, respectively, and the overall positioning accuracy of key nodes whose movement state exhibits major changes improves by more than 20%. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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17 pages, 11051 KiB

Open AccessArticle

Performance of DGPS Smartphone Positioning with the Use of P(L1) vs. P(L5) Pseudorange Measurements

by Mieczysław Bakuła, Marcin Uradziński and Kamil Krasuski

Remote Sens. 2022, 14(4), 929; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14040929 - 14 Feb 2022

Cited by 11 | Viewed by 3563

Abstract

This paper presents numerical analyzes of code differential GPS positioning with the use of two Huawei P30 Pro mobile phones. Code observations on L1 and L5 frequencies were chosen for DGPS positioning analysis. For project purposes, we additionally used one high-class geodetic GNSS receiver (Javad Alpha) acting as a reference station. Smartphones were placed at the same distance of 0.5 m from the reference receiver. Such a close distance was specially planned by the authors in order to achieve identical observation conditions. Thus, it was possible to compare the DGPS positioning accuracy using the same satellites and the P(L1) and P(L5) code only, for single observation epochs and for sequential DGPS adjustment. Additionally, the precision of observations of the second differences in the observations P(L1) and P(L5) was analyzed. In general, the use of the P(L5) code to derive DGPS positions has made it possible to significantly increase the accuracy with respect to the positions derived using the P(L1) code. Average errors of horizontal and vertical coordinates were about 60–80% lower for the DGPS solution using the P(L5) code than using the P(L1) code. Based on the simulated statistical analyses, an accuracy of about 0.4 m (3D) with 16 satellites may be obtained using a smartphone with P(L5) code. An accuracy of about 0.3 m (3D) can be achieved with 26 satellites. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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19 pages, 3839 KiB

Open AccessArticle

Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone

by Min Li, Zhuo Lei, Wenwen Li, Kecai Jiang, Tengda Huang, Jiawei Zheng and Qile Zhao

Remote Sens. 2021, 13(23), 4894; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13234894 - 02 Dec 2021

Cited by 15 | Viewed by 2513

Abstract

The opening access of global navigation satellite system (GNSS) raw data in Android smart devices has led to numerous studies on precise point positioning on mobile phones, among which single-frequency precise point positioning (SF-PPP) has become popular because smartphone-based dual-frequency data still suffer from poor observational quality. As the ionospheric delay is a dominant factor in SF-PPP, we first evaluated two SF-PPP approaches with the MGEX (Multi-GNSS Experiment) stations, the Group and Phase Ionospheric Correction (GRAPHIC) approach and the uncombined approach, and then applied them to a Huawei P40 smartphone. For MGEX stations, both approaches achieved less than 0.1 m and 0.2 m accuracy in horizontal and vertical components, respectively. Uncombined SF-PPP manifested a significant decrease in the convergence time by 40.7%, 20.0%, and 13.8% in the east, north, and up components, respectively. For P40 data, the SF-PPP performance was analyzed using data collected with both a built-in antenna and an external geodetic antenna. The P40 data collected with the built-in antenna showed lower carrier-to-noise ratio (C/N0) values, and the pseudorange noise reached 0.67 m, which is about 67% larger than that with a geodetic antenna. Because the P40 pseudorange noise presented a strong correlation with C/N0, a C/N0-dependent weight model was constructed and used for the P40 data with the built-in antenna. The convergence of uncombined SF-PPP approach was faster than the GRAPHIC model for both the internal and external antenna datasets. The root mean square (RMS) errors for the uncombined SF-PPP solutions of P40 with an external antenna were 0.14 m, 0.15 m, and 0.33 m in the east, north, and up directions, respectively. In contrast, the P40 with an embedded antenna could only reach 0.72 m, 0.51 m, and 0.66 m, respectively, indicating severe positioning degradation due to antenna issues. The results indicate that the two SF-PPP models both can achieve sub-meter level positioning accuracy utilizing multi-GNSS single-frequency observations from mobile smartphones. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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22 pages, 7227 KiB

Open AccessArticle

Preliminary Results on Tropospheric ZTD Estimation by Smartphone

by Lorenzo Benvenuto, Paolo Dabove, Ilaria Ferrando and Domenico Sguerso

Remote Sens. 2021, 13(22), 4567; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13224567 - 13 Nov 2021

Cited by 6 | Viewed by 2295

Abstract

The Global Navigation Satellite System (GNSS) receiver is one of the many sensors embedded in smartphones. The early versions of the Android operating system could only access limited information from the GNSS, allowing the related Application Program Interface (API) to obtain only the location. With the development of the Android 7.0 (Nougat) operating system in May 2016, raw measurements from the internal GNSS sensor installed in the smartphone could be accessed. This work aims to show an initial analysis regarding the feasibility of Zenith Total Delay (ZTD) estimation by GNSS measurements extracted from smartphones, evaluating the accuracy of estimation to open a new window on troposphere local monitoring. Two different test sites have been considered, and two different types of software for data processing have been used. ZTDs have been estimated from both a dual-frequency and a multi-constellation receiver embedded in the smartphone, and from a GNSS Continuously Operating Reference Station (CORS). The results have shown interesting performances in terms of ZTD estimation from the smartphone in respect of the estimations obtained with a geodetic receiver. Full article

(This article belongs to the Special Issue Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications)

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Smartphone-Derived GNSS Measurements Characterization for Precise Positioning and Navigation Applications

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