Crespi M.

Li X.

Paziewski J.

English

Archivio della ricerca- Università di Roma La Sapienza

remote sensing  EditorialEditorial for the Special Issue: “High-Precision GNSS:Methods, Open Problems and Geoscience Applications”Xingxing Li 1,*, Jacek Paziewski 2 and Mattia Crespi 31 School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430079, China2 The Faculty of Geodesy, Geospatial and Civil Engineering Institute of Geodesy, University of Warmia andMazury in Olsztyn (UWM), 10-719 Olsztyn, Poland; jacek.paziewski@uwm.edu.pl3 Geodesy and Geomatics Division—DICEA, Sapienza University of Rome, 00184 Rome, Italy;mattia.crespi@uniroma1.it* Correspondence: xxli@sgg.whu.edu.cnReceived: 17 April 2020; Accepted: 18 April 2020; Published: 18 May 2020Keywords: GNSS; GPS; GLONASS; Galileo; BDS; precise point positioning; relative positioning;orbit determination; ionosphere sounding; troposphere sounding; geoscience applications; high-ratepositioning; GNSS for geodynamicsIn the past two decades, the high-precision Global Positioning System (GPS) has significantlyincreased the range of geoscience applications and their precision. Currently, it is one of two fullyoperational Global Navigation Satellite Systems (GNSS), and two more are in the implementation stage.The new European Galileo and Chinese BeiDou Navigation Satellite System (BDS) already provideusable signals, and both GPS and GLONASS are currently undergoing significant modernization,which adds more capacity, more signals, better accuracy, and interoperability, etc.Meanwhile, there has been significant technological development in GNSS equipment (in somecases, even at low-cost), which is now able to collect measurements at much higher rates (up to 100 Hz),thus presenting new possibilities. On the one hand, the new developments in GNSS offer a broad rangeof new applications for solid and fluid Earth investigations, in both post-processing and real-time;on the other, this results in new problems and challenges in data processing that increase the need forGNSS research. Algorithmic advancements are needed to address the opportunities and challenges inenhancing the accuracy, availability, interoperability, and integrity of high-precision GNSS applications.This special issue aims to provide an overview of the potential of high-precision GNSS forgeoscience applications. Besides discussing the current developments in high-precision GNSSconstellations, signals and algorithms devoted to Precise Point Positioning (PPP) and Precise OrbitDetermination (POD), the special issue focuses on the use of high-precision GNSS in diverse geoscienceapplications, in terms of geodynamics, seismology, tsunamis, ionosphere, troposphere, etc. An overviewof the contributions in this special issue is given in the following paragraphs.Since December 2018, the third generation of BDS (BDS-3) started to provide global-coveragepositioning, navigation and timing (PNT) services. The studies conducted on the new BDS satellitesand redesigned signals have indicated that the signal in space range error (SISRE) of BDS-3 is superiorto that of BDS-2 [1] and the atomic clock has better frequency stability than GPS BLOCK IIF satellites [2].Among the four open service BDS signals B1I, B1C, B2a and B3I, the ionosphere-free (IF) combinationof B1C-B2a was recommended for precise GNSS data processing in regard to the noise amplitudeand compatibility with other GNSS. Further research demonstrated that 50%–60% improvements inposition accuracy in the east component could be obtained by performing PPP ambiguity resolution(AR) with BDS and Galileo triple-frequency observations, with respect to those achievable with the floatsolution [3]. Besides the discussion of developments in the GNSS in this special issue, five currentlyRemote Sens. 2020, 12, 1602; doi:10.3390/rs12101602 www.mdpi.com/journal/remotesensingRemote Sens. 2020, 12, 1602 2 of 5available satellite-based augmentation systems (SBASs) were also evaluated in terms of their orbit,clock and ionosphere corrections [4].Several studies included in this special issue are dedicated to the advancement of GNSS algorithmsand models. Qu et al. [5] proposed a modified least-squares collocation algorithm (LSC) by combiningthe distance scale factor and adaptive adjustment. The new LSC algorithm better reflects thecharacteristics of GPS crustal movement and was thus valuable for analysis of regional tectonicdynamics. Wei et al. [6] presented a new cycle slip detection and repair approach for high-dynamiclow-earth-orbit (LEO) satellites by making use of second-order time-difference geometry-free (STG)phase combinations. Understanding the characteristics of diverse biases in GNSS data processingis crucial for the refinement of current GNSS algorithms and models. Wu et al. [7] investigated,for the first time, the size and stability of phase and code differential inter-system bias (ISB) betweenBDS-3/GPS/Galileo for tightly combined real-time kinematics (RTK). The characteristics of atmosphereand broadcast ephemeris errors in short baseline RTK were also systematically analyzed in [8]. In regardto code bias, the time-varying characteristic of the GPS differential code bias (DCB) was investigatedusing triple-frequency observations in [9]. As for the phase bias, Wang et al. [10] constructed anew computationally efficient ambiguity acceptance test with a controllable success fix rate, namely,the fixed likelihood-ratio (FL) approach, which does not require Monte Carlo simulation. Focusing onthe mathematical method of error modeling, Li et al. [11] employed independent component analysis(ICA) to remove the common mode error and select the optimal noise model for the GNSS coordinatetime series by using observations from 79 GPS stations in Antarctica from 2010 to 2018.Precise orbit information for GNSS satellites is the basis for high-precision GNSS applications.In this special issue, several studies were carried out to improve GNSS POD accuracy. Aiming toshorten the interruption period of BDS broadcast ephemerides after satellite maneuverings andimprove the ephemeris accuracy, Qiao et al. [12] proposed a two-step orbit recovery strategy based ona piecewise linear thrust model. In another contribution from Ye et al. [13], the authors presented athree-step method for determining unhealthy time periods of GPS satellite orbit in broadcast ephemerisduring POD to provide reliable information in near-real time. For the purpose of improving theultra-rapid orbit accuracy for BDS-2/BDS-3, Wang et al. [14] linked the predicted clock offsets into thePOD as constraints to strengthen the estimation. By making use of SLR Normal Points (NPs) data only,Yang et al. [15] performed the POD of BDS-2/BDS-3 and found 3D RMS values of 9-day overlaps of 0.49and 1.89 m for BDS MEO and IGSO satellites, respectively. GNSS orbits are traditionally determined byobservation data from ground stations, which usually need even global distribution to ensure adequateobservation geometry strength. In order to overcome the weakness in the tracking geometry of groundstations, Li et al. [16] designed six different LEO constellations to enhance the GNSS POD and achieveda notable improvement in accuracy of over 70% compared with ground-based POD. As for the LEOPOD, the potential of the use of inter-satellite link (ISL) was demonstrated in [17]. Gong et al. [18]focused on the onboard real-time POD for low-cost single-frequency GNSS receivers and developed aseries POD strategy.Along with up-to-date GNSS signals, equipment and precise orbit/clock products, the positioningaccuracy of GNSS is undoubtedly a major concern. Relative positioning and PPP are two generalpositioning methods. Katsigianni et al. [19] demonstrated that the Galileo-only constellation is alreadyable to achieve comparable PPP accuracy with GPS, and the accuracy can be further improved bycombining GPS/Galileo observations or performed ambiguity resolution (AR). By making use of thefusion of three designed LEO constellation and GNSS, Li et al. [20] shortened the time to first fix(TTFF) of multi-frequency PPP AR to less than 5 minutes and over 60% accuracy improvement couldbe obtained with the LEO augmentation. As for relative positioning, Chen et al. [21] developed aninter-system phase ambiguity fixing method based on un-difference (UD) observations by calculatingthe inter-system phase bias. In addition, the performance of GPS/Galileo relative positioning for bridgedynamic monitoring was demonstrated [22].Remote Sens. 2020, 12, 1602 3 of 5In particular, the use of GNSS in specific geoscience applications is discussed in this specialissue. As an important application of PPP, the current performance of multi-GNSS PPP time andfrequency transfer was evaluated using different GNSS constellation and precise orbit/clock productsin [23]. In regard to geodynamics, Zheng et al. [24] applied sidereal filtering in the GNSS observationdomain to alleviate the centimeter-level PPP noise using multi-GNSS data during the 2017 Mw 6.5Jiuzhaigou earthquake. The PPP method was also used to study the activity of the Long Point Fault inHouston, Texas with six-years of continuous GPS observations [25]. In this respect, a Stable CaribbeanReference Frame 2018 (CARIB18) using long-term continuous GPS observations was developed andintroduced [26]. Research in this special issue is also concerned about glacier and climate change.Continuous GPS observations were employed for 14 years to investigate the ice flow velocity in [27].By analyzing the vertical position time series from 469 European GPS stations, the post-glacial rebound(PGR) in Europe was comprehensively investigated in [28]. Moreover, Wu et al. [29] estimated thesatellite accelerations directly from the onboard GPS data using the point-wise acceleration approachfor the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite, and achievedhigher gravity field model accuracy than those derived from kinematic orbits.Precise modeling of the refraction caused by the troposphere and ionosphere is also a topicof interest in this special issue. Sun et al. [30] proposed a new empirical model for estimating thetropospheric delay and atmospheric weight mean temperature by using ERA-interim reanalysis data.Zus et al. [31] improved the GNSS zenith wet delay (ZWD) interpolation by utilizing troposphericgradients. In terms of ionospheric delays, Wang et al. [32] evaluated the performance of fourionospheric models in Multi-GNSS single-frequency positioning over China. Furthermore, with therapid development of sensors in mobile phones, the most up-to-date phones were reported to becapable of real-time ionosphere monitoring [33].Acknowledgments: The Guest Editor of this Special Issue would like to thank all authors who have contributedto this volume for sharing their scientific results and for their excellent collaboration. Special thanks are due to thecommunity of distinguished reviewers for their valuable and insightful inputs. The Remote Sensing editorial teamis gratefully acknowledged for its support during all phases of the endeavor to successfully complete this volume.Conflicts of Interest: The authors declare no conflict of interest.References1. Zhang, Y.; Kubo, N.; Chen, J.; Wang, J.; Wang, H. Initial Positioning Assessment of BDS New Satellites andNew Signals. Remote Sens. 2019, 11, 1320. [CrossRef]2. Xu, X.; Wang, X.; Liu, J.; Zhao, Q. Characteristics of BD3 Global Service Satellites: POD, Open Service Signaland Atomic Clock Performance. Remote Sens. 2019, 11, 1559. [CrossRef]3. Xiao, G.; Li, P.; Gao, Y.; Heck, B. A Unified Model for Multi-Frequency PPP Ambiguity Resolution and TestResults with Galileo and BeiDou Triple-Frequency Observations. Remote Sens. 2019, 11, 116. [CrossRef]4. Nie, Z.; Zhou, P.; Liu, F.; Wang, Z.; Gao, Y. Evaluation of Orbit, Clock and Ionospheric Corrections from FiveCurrently Available SBAS L1 Services: Methodology and Analysis. Remote Sens. 2019, 11, 411. [CrossRef]5. Qu, W.; Chen, H.; Liang, S.; Zhang, Q.; Zhao, L.; Gao, Y.; Zhu, W. Adaptive Least-Squares CollocationAlgorithm Considering Distance Scale Factor for GPS Crustal Velocity Field Fitting and Estimation.Remote Sens. 2019, 11, 2692. [CrossRef]6. Wei, H.; Li, J.; Zhang, S.; Xu, X. Cycle Slip Detection and Repair for Dual-Frequency LEO Satellite GPSCarrier Phase Observations with Orbit Dynamic Model Information. Remote Sens. 2019, 11, 1273. [CrossRef]7. Wu, M.; Liu, W.; Wang, W.; Zhang, X. Differential Inter-System Biases Estimation and Initial Assessment ofInstantaneous Tightly Combined RTK with BDS-3, GPS, and Galileo. Remote Sens. 2019, 11, 1430. [CrossRef]8. Shu, B.; Liu, H.; Feng, Y.; Xu, L.; Qian, C.; Yang, Z. Analysis of Factors Affecting Asynchronous RTKPositioning with GNSS Signals. Remote Sens. 2019, 11, 1256. [CrossRef]9. Li, H.; Xiao, J.; Zhu, W. Investigation and Validation of the Time-Varying Characteristic for the GPS DifferentialCode Bias. Remote Sens. 2019, 11, 428. [CrossRef]10. Wang, L.; Chen, R.; Shen, L.; Zheng, F.; Feng, Y.; Guo, J. A Controllable Success Fix Rate ThresholdDetermination Method for GNSS Ambiguity Acceptance Tests. Remote Sens. 2019, 11, 804. [CrossRef]Remote Sens. 2020, 12, 1602 4 of 511. Li, W.; Li, F.; Zhang, S.; Lei, J.; Zhang, Q.; Yuan, L. Spatiotemporal Filtering and Noise Analysis for RegionalGNSS Network in Antarctica Using Independent Component Analysis. Remote Sens. 2019, 11, 386. [CrossRef]12. Qiao, J.; Chen, W.; Ji, S.; Weng, D. Accurate and Rapid Broadcast Ephemerides for Beidou-ManeuveredSatellites. Remote Sens. 2019, 11, 787. [CrossRef]13. Ye, F.; Yuan, Y.; Zhang, B.; Tan, B.; Ou, J. A Three-Step Method for Determining Unhealthy Time Period ofGPS Satellite Orbit in Broadcast Ephemeris and Its Preliminary Applications for Precise Orbit Determination.Remote Sens. 2019, 11, 1098. [CrossRef]14. Wang, Q.; Hu, C.; Zhang, K. A BDS-2/BDS-3 Integrated Method for Ultra-Rapid Orbit Determination withthe Aid of Precise Satellite Clock Offsets. Remote Sens. 2019, 11, 1758. [CrossRef]15. Yang, H.; Xu, T.; Nie, W.; Gao, F.; Guan, M. Precise Orbit Determination of BDS-2 and BDS-3 Using SLR.Remote Sens. 2019, 11, 2735. [CrossRef]16. Li, X.; Zhang, K.; Ma, F.; Zhang, W.; Zhang, Q.; Qin, Y.; Zhang, H.; Meng, Y.; Bian, L. Integrated Precise OrbitDetermination of Multi-GNSS and Large LEO Constellations. Remote Sens. 2019, 11, 2514. [CrossRef]17. Li, X.; Jiang, Z.; Ma, F.; Lv, H.; Yuan, Y.; Li, X. LEO Precise Orbit Determination with Inter-satellite Links.Remote Sens. 2019, 11, 2117. [CrossRef]18. Gong, X.; Guo, L.; Wang, F.; Zhang, W.; Sang, J.; Ge, M.; Schuh, H. Precise Onboard Real-Time OrbitDetermination with a Low-Cost Single-Frequency GPS/BDS Receiver. Remote Sens. 2019, 11, 1391. [CrossRef]19. Katsigianni, G.; Loyer, S.; Perosanz, F. 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Optimal Strategy of a GPS Position Time Series Analysis for Post-GlacialRebound Investigation in Europe. Remote Sens. 2019, 11, 1209. [CrossRef]29. Wu, T.; Li, J.; Xu, X.; Wei, H.; Kuang, K.; Zhao, Y. Gravity Field Model Determination Based on GOCE SatellitePoint-Wise Accelerations Estimated from Onboard Carrier Phase Observations. Remote Sens. 2019, 11, 1420.[CrossRef]30. Sun, Z.; Zhang, B.; Yao, Y. A Global Model for Estimating Tropospheric Delay and Weighted MeanTemperature Developed with Atmospheric Reanalysis Data from 1979 to 2017. Remote Sens. 2019, 11, 1893.[CrossRef]31. Zus, F.; Douša, J.; Kačmařík, M.; Václavovic, P.; Balidakis, K.; Dick, G.; Wickert, J. Improving GNSS ZenithWet Delay Interpolation by Utilizing Tropospheric Gradients: Experiments with a Dense Station Network inCentral Europe in the Warm Season. Remote Sens. 2019, 11, 674. [CrossRef]Remote Sens. 2020, 12, 1602 5 of 532. Wang, A.; Chen, J.; Zhang, Y.; Meng, L.; Wang, J. Performance of Selected Ionospheric Models in Multi-GlobalNavigation Satellite System Single-Frequency Positioning over China. Remote Sens. 2019, 11, 2070. [CrossRef]33. Fortunato, M.; Ravanelli, M.; Mazzoni, A. Real-Time Geophysical Applications with Android GNSS RawMeasurements. Remote Sens. 2019, 11, 2113. [CrossRef]© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Editorial for the special issue: "High-precision GNSS: Methods, open problems and geoscience applications"

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Editorial for the special issue: "High-precision GNSS: Methods, open problems and geoscience applications"

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