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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 11228

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Special Issue Editors

Prof. Dr. Junping Chen

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Guest Editor

Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
Interests: GNSS data analysis including POD; clock analysis; SBAS; PPP; PPP-RTK; LEO augmentation; reference frame and geodynamics
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Dr. Bingbing Duan

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Guest Editor

Institute for Astronomical and Physical Geodesy, Technical University of Munich, Arcisstr 21, 80333 Munich, Germany
Interests: GNSS orbit modeling; precise GNSS orbit determination; GNSS signal biases; PPP-AR; LEO satellite orbit determination, and the combination of space techniques (GNSS, DORIS, SLR, VLBI)
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Dr. Jungang Wang

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Guest Editor

GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Interests: space geodetic techniques; global navigation satellite systems; atmospheric delay modeling; precise orbit determination
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Dr. Yize Zhang

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Guest Editor

Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
Interests: GNSS precise point positioning; GNSS ambiguity resolution; GNSS bias estimation
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Dr. Bin Wang

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Guest Editor

Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
Interests: precise timing and time transfer

Dr. Micaela Troglia Gamba

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Guest Editor

Leonardo S.p.A., Strada Privata Aeroporto Caselle, San Maurizio Canavese 10077, TO, Italy
Interests: real-time GNSS; GNSS software receivers; signal processing; prototyping
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Special Issue Information

Dear Colleagues,

In the past several decades, we have witnessed the rapid development of global navigation satellite systems (GNSS), including both global (GPS, GLONASS, Galileo, and BDS) and regional (QZSS and IRNSS) systems. The technological developments of the new constellations, including high-precision clocks onboard Galileo, BDS-3, and GPS Block III satellites, the inter-satellite-link of BDS-3, multi-frequency, and low Earth orbiter (LEO) augmentation have improved the accuracy, robustness, and reliability of GNSS. These advances, on the one hand, promote the applications of GNSS in PNT (positioning, navigation, and timing) and geosciences, and on the other hand require innovative methods and algorithms to improve the data processing strategy.

This Special Issue aims to publish studies on the development of GNSS, including GPS, GLONASS, Galileo, and in particular BDS. A variety of topics are of interest, from GNSS data processing (including satellite orbit and clock determination, ambiguity resolution, optimal modeling strategies of atmospheric delays, precise point positioning (PPP), and real-time kinematic positioning (RTK)) to the applications of GNSS in geosciences such as geohazard monitoring and early warning, and environment monitoring (ionosphere, troposphere, and local environment). The new technological developments and applications of BDS3 and LEO PNT are of high interest. Both research articles and review papers are welcome.

Prof. Dr. Junping Chen
Dr. Bingbing Duan
Dr. Jungang Wang
Dr. Yize Zhang
Dr. Bin Wang
Dr. Micaela Troglia Gamba
Guest Editors

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

GNSS
BDS
LEO PNT
precise orbit determination
precise point positioning
regional augmentation
atmospheric delay modeling
PPP/iPPP time transfer

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Published Papers (7 papers)

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Research

17 pages, 6437 KiB

Open AccessArticle

Constructing a Regional Ionospheric TEC Model in China with Empirical Orthogonal Function and Dense GNSS Observation

by Bo Xiong, Yuxiao Li, Changhao Yu, Xiaolin Li, Jianyong Li, Biqiang Zhao, Feng Ding, Lianhuan Hu, Yuxin Wang and Lingxiao Du

Remote Sens. 2023, 15(21), 5207; https://doi.org/10.3390/rs15215207 - 2 Nov 2023

Cited by 1 | Viewed by 1238

Abstract

Using Global Navigation Satellite Systems (GNSS) observation data for developing a high-precision ionospheric Total Electron Content (TEC) model is one of the essential subjects in ionospheric physics research and the application of satellite navigation correction. In this study, we integrate the Empirical Orthogonal Function (EOF) method with the TEC data provided by the Center for Orbit Determination in Europe (CODE), and observed by the dense GNSS receivers operated by the Crustal Movement Observation Network of China (CMONOC) to construct a regional ionospheric TEC model over China. The EOF analysis of CODE TEC in China from 1998 to 2010 shows that the first-order EOF component accounts for 90.3813% of the total variation of the ionospheric TEC in China. Meanwhile, the average value of CODE TEC is consistent with the spatial and temporal distribution characteristics of the first-order EOF base function, which mainly reflects the latitude and diurnal variations of TEC in China. The first-order coefficient after EOF decomposition shows an obvious 11-year period and semi-annual variations. The maximum amplitude of semi-annual variation mainly appears in March and October, which is closely associated with the variation in geographical longitude, the semi-annual change of the low-latitude electric field, and the ionospheric fountain effect. The second-order coefficient has an evident annual variation, the minimum amplitude mainly occurs in March, August, and September, and the amplitude values in the high solar activity years are more significant than those in the low solar activity years. The third-order coefficient mainly shows the characteristics of annual variation, and the fourth-order coefficient shows the noticeable semi-annual and annual variations. The third and fourth-order coefficients are both modulated by the solar activity index F10.7. The ionospheric TEC model in China, driven by CMONOC real-time GNSS observation data, can better reflect the latitude, local time and seasonal variation characteristics of ionospheric TEC over China. In particular, it can clearly show the spring and autumn asymmetry of ionospheric TEC in the low latitudes. The root mean square error of the absolute error between the model and the actual observation is mainly distributed around 2.45 TECU (1 TECU = 10¹⁶ electrons/m²). The values of the TEC model constructed in this study are closer to the actual observed values than those of the CODE TEC in China. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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18 pages, 11903 KiB

Open AccessArticle

Improved Medium Baseline RTK Positioning Performance Based on BDS/Galileo/GPS Triple-Frequency-Only Observations

by Xifeng Dang, Xiao Yin, Yize Zhang, Chengfa Gao, Jincheng Wu and Yongqiang Liu

Remote Sens. 2023, 15(21), 5198; https://doi.org/10.3390/rs15215198 - 1 Nov 2023

Cited by 1 | Viewed by 1654

Abstract

With the global service of the BeiDou Navigation Satellite System (BDS), the Galileo Navigation Satellite System (Galileo), and the modernization of the Global Positioning System (GPS), achieving high-precision positioning through triple-frequency-only observations in medium baseline real-time kinematics (RTK) is anticipated. This study investigates the impacts of double-difference (DD) troposphere delay and ionosphere delay on ambiguity resolution (AR) based on six medium baselines at a latitude of 30°. Additionally, it evaluates positioning accuracy, fixing rate, convergence time, and computational time using triple-frequency-only (B1I/B2a/B3I, E1/E5a/E5b, L1/L2/L5) data, comparing these results to those obtained from dual-frequency (B1I/B2a, E1/E5a, L1/L2) and combined dual-frequency and triple-frequency data. The experimental findings suggest that, for geometry-based wide-lane (WL) AR, the DD troposphere delay and ionosphere delay can be disregarded. However, they cannot be overlooked when aiming to resolve the raw ambiguity. Triple-frequency-only RTK exhibits comparable positioning accuracy to dual-frequency RTK, with its primary advantage lying in faster convergence. The probability of achieving convergence within 180 s is approximately 8.0% higher for triple-frequency-only RTK compared to dual-frequency RTK. In terms of computational time, the use of triple-frequency-only data reduces the required time by 8.26 s compared to the approach that simultaneously employs both dual-frequency and triple-frequency data, resulting in a computational time reduction of approximately 20%. Therefore, when conducting medium baseline RTK positioning, it is recommended to adopt the ambiguity resolution method proposed in this paper based on triple-frequency-only observations. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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16 pages, 1060 KiB

Open AccessCommunication

Robust Space-Time Adaptive Processing Method for GNSS Receivers in Coherent Signal Environments

by Zhen Meng and Feng Shen

Remote Sens. 2023, 15(17), 4212; https://doi.org/10.3390/rs15174212 - 27 Aug 2023

Cited by 2 | Viewed by 1319

Abstract

In the coherent signal environments caused by multipath propagation, the interference suppression performance of the global navigation satellite systems (GNSS) receivers decreases sharply. In this paper, a robust space-time adaptive processing (STAP) method for GNSS receivers is proposed to suppress interferences in coherent signal environments, by using the modified space-time two-dimensional iterative adaptive approach (ST2D-IAA) spectrum estimation. This method applies the IAA algorithm to the ST2D signal model of GNSS receivers, and further modifies the ST2D-IAA algorithm to accurately estimate the power spectrum and noise power simultaneously. The space-time interference-plus-noise covariance matrix (STINCM) is reconstructed by using the estimated power spectrum and noise power in the interference angle region. Based on the reconstructed STINCM, we construct the STAP beamforming optimization problem for the space-time steering vector (STSV) error vector, and further correct the STSV of GNSS signal. Finally, the weight vector of STAP beamforming is calculated by using the reconstructed STINCM and the corrected STSV of GNSS signal. Simulation results show that the proposed method can suppress interferences in coherent signal environments and outperforms the current methods. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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16 pages, 4372 KiB

Open AccessArticle

Assessing the Nonlinear Changes in Global Navigation Satellite System Vertical Time Series with Environmental Loading in Mainland China

by Jie Zhang, Zhicai Li, Peng Zhang, Fei Yang, Junli Wu, Xuchun Liu, Xiaoqing Wang and Qianchi Tan

Remote Sens. 2023, 15(16), 4115; https://doi.org/10.3390/rs15164115 - 21 Aug 2023

Cited by 1 | Viewed by 1398

Abstract

This study investigated the nonlinear changes in the vertical motion of 411 GNSS reference stations situated in mainland China and assessed the influence of the environmental load on their vertical displacement. The researchers evaluated the effect of environmental load by calculating the change in annual cycle amplitude before and after its removal, focusing on its impact across regions with distinct foundation types. The results demonstrate that removing the environmental load led to a considerable reduction of approximately 50.25% in the annual cycle amplitude of vertical motion for GNSS reference stations in mainland China. This reduction in amplitude improved the positioning accuracy of the stations, with the highest WRMS reduction being 2.72 mm and an average reduction of 1.03 mm. The most significant impact was observed in the southwestern, northern, and northwestern regions, where the amplitude experienced a notable decrease. Conversely, the southeastern region exhibited a corresponding increase in amplitude. This article innovatively explored the effects of environmental loads on diverse foundation types. When categorizing GNSS reference stations based on their foundation type, namely, bedrock, 18 m soil layer, and 4–8 m soil layer stations, this study found that removing the environmental load resulted in reductions in annual cycle amplitudes of 49.37%, 59.61%, and 46.48%, respectively. These findings indicate that 18 m soil layer stations were more susceptible to environmental load-induced vertical motion. In conclusion, the impact of the environmental load was crucial when analyzing the vertical motion of GNSS reference stations in mainland China, as it was essential for establishing a high-precision coordinate reference framework and studying the tectonic structure of the region. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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23 pages, 15582 KiB

Open AccessArticle

Tropospheric Delay Parameter Estimation Strategy in BDS Precise Point Positioning

by Zhimin Liu, Yan Xu, Xing Su, Cuilin Kuang, Bin Wang, Guangxing Wang and Hongyang Ma

Remote Sens. 2023, 15(15), 3880; https://doi.org/10.3390/rs15153880 - 4 Aug 2023

Viewed by 1496

Abstract

Tropospheric delay (TD) parameter estimation is a critical issue underlying high-precision data processing for global navigation satellite systems (GNSSs). The most widely used TD parameter estimation methods are the random walk (RW) and piece-wise constant (PWC). The RW method can effectively track rapid variations of tropospheric delay, but it may introduce excessive noise. In contrast, the PWC method introduces less noise, but it is less adaptable to cases of large variations of tropospheric delay. To address the problem of how to choose the optimal TD parameter estimation method, this paper investigates the variation patterns of international GNSS service zenith tropospheric delay (IGS ZTD) products and proposes a combined strategy model for TD parameter estimation. Firstly, this paper avoids the day-boundary jumps problem of IGS ZTD products by grouping based on single-day data. Secondly, this paper introduces discrete point areas (DPAs) to measure the magnitude of the ZTD values and uses comprehensive indicators to reflect the variation of ZTD. Next, based on the Köppen-Geiger climate classification, this study selected five different climate classifications with a total of 20 IGS stations as experimental data. The data assessed span from day of year (DOY) 001 to DOY 365 in 2022. This paper then applied 26 different parameter estimation strategies for static precise point positioning (PPP) data processing, and the parameter estimation strategies that were used include the RW and PWC (with the piece-wise constant ranging from twenty minutes to five hundred minutes at twenty-minute intervals). Finally, ZTD and positioning results were obtained using various parameter estimation methods, and a combined strategy model was established. We selected five different climate classifications of IGS stations as validation data and designed three sets of comparative experiments: RW, PWC120, and the combined strategy model, to verify the effectiveness of the combined strategy model. The experimental results revealed that: RW and the combined strategy model have a comparable ZTD accuracy and both are superior to PWC120. The combined strategy model improves the positioning accuracy in the U direction compared to RW and PWC120. In arid (B) and polar (E) regions with a small variation of TD, the PWC120 strategy displayed a better positioning accuracy than the RW strategy; in equatorial (A) and warm-temperate (C) regions, where there are large variations of TD, the RW strategy exhibited a better positioning accuracy than the PWC120 strategy. The combined strategy model can flexibly select the optimal parameter estimation method according to the comprehensive indicator while ensuring ZTD estimation accuracy; it enhances positioning accuracy. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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22 pages, 4118 KiB

Open AccessArticle

Single-Epoch Decimeter-Level Precise Point Positioning with a Galileo Five-Frequency Ionosphere-Reduced Combination

by Qing Zhao, Shuguo Pan, Ji Liu, Yin Lu, Peng Zhang and Wang Gao

Remote Sens. 2023, 15(14), 3562; https://doi.org/10.3390/rs15143562 - 15 Jul 2023

Cited by 1 | Viewed by 1329

Abstract

Currently, there are two main methods for single-epoch decimeter-level precise point positioning (PPP); one is a model based on ambiguity-fixed ionosphere-free (AFIF) observations, and the other is based on uncombined (UC) PPP. The implementation of these two models requires both extra-wide-lane (EWL) and wide-lane (WL) ambiguity fixing. Different from the existing methods, this paper proposes a multi-frequency ionosphere-reduced (IR) PPP model suitable for single-epoch decimeter-level positioning. Based on Galileo five-frequency data, the optimal selection strategy of IR combinations is first studied with ionosphere, noise level and wavelength factors considered. Then, based on the selected IR combination, two IR PPP models, namely IR(EST) and IR(IGN), are established according to whether ionosphere parameters are estimated or ignored. Finally, the proposed models are verified with real tracked data from globally distributed stations, and further compared with the existing AFIF/UC models in terms of positioning performance and time consumption. The relationship between the ionosphere equivalent ranging error and satellite elevation in the IR models is analyzed. The lower the elevation is, the larger the residual ranging error is, and its impact on positioning is weakened by downweighting its observations and adjusting the cut-off elevation during the partial ambiguity fixing (PAF) process. The results show that the performance of the two IR models is basically the same, and both can achieve horizontal and vertical accuracies better than 20 cm and 40 cm, respectively. Compared with the existing AFIF/UC models, the proposed IR models can achieve similar decimeter-level accuracy with only one step of EWL ambiguity fixing, and at the same time, the IR models have varying degrees of improvement in time consumption: 38% shorter than the AFIF model and 97% shorter than the UC model. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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22 pages, 6511 KiB

Open AccessArticle

Region-Specific and Weather-Dependent Characteristics of the Relation between GNSS-Weighted Mean Temperature and Surface Temperature over China

by Minghua Wang, Junping Chen, Jie Han, Yize Zhang, Mengtian Fan, Miao Yu, Chengzhi Sun and Tao Xie

Remote Sens. 2023, 15(6), 1538; https://doi.org/10.3390/rs15061538 - 11 Mar 2023

Cited by 2 | Viewed by 1810

Abstract

Weighted mean temperature of the atmosphere,

T_{m}

, is a key parameter for retrieving the precipitable water vapor from Global Navigation Satellite System observations. It is commonly estimated by a linear model that relates to surface temperature

T_{s}

. However, the [...] Read more.

Weighted mean temperature of the atmosphere,

T_{m}

, is a key parameter for retrieving the precipitable water vapor from Global Navigation Satellite System observations. It is commonly estimated by a linear model that relates to surface temperature

T_{s}

. However, the linear relationship between

T_{m}

and

T_{s}

is associated with geographic regions and affected by the weather. To better estimate the

T_{m}

over China, we analyzed the region-specific and weather-dependent characteristics of this linear relationship using 860,054 radiosonde profiles from 88 Chinese stations between 2005 and 2018. The slope coefficients of site-specific linear models are 0.35~0.95, which generally reduce from northeast to southwest. Over southwest China, the slope coefficient changes drastically, while over the northwest, it shows little variation. We developed a

T_{s} \sim T_{m}

linear model using the data from rainless days as well as a model using the data from rainy days for each station. At half the stations, mostly located in west and north China, the differences between the rainy-day and rainless-day

T_{m}

models are significant and larger than 0.5% (1%) in mean (maximal) relative bias. The regression precisions of the rainy-day models are higher than that of the rainless-day models averagely by 28% for the stations. Radiosonde data satisfying

T_{m} - T_{s} > 10 K

and

T_{s} - T_{m} > 30 K

most deviate from linear regression models. Results suggest that the former situation is related to low surface temperature (<270 K), as well as striking temperature and humidity inversions below 800 hPa, while the latter situation is related to high surface temperature (>280 K) and a distinct humidity inversion above 600 hPa. Full article

(This article belongs to the Special Issue New Progress in GNSS Data Processing Technology and Modeling)

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