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Precise Point Positioning with GPS, GLONASS, BeiDou, and Galileo II

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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 (30 June 2023) | Viewed by 7276

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Special Issue Editors

Dr. Shengfeng Gu

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GNSS Research Center, Wuhan University, Luoyu Road 129, Wuhan 430079, China
Interests: GNSS real-time precise data processing; GNSS ionospheric delay modeling; navigation
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Dr. Xiaopeng Gong

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GNSS Research Center, Wuhan University, Luoyu Road 129, Wuhan 430079, China
Interests: GNSS real-time clock estimation; precise positioning; signal bias estimation
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Prof. Dr. Yidong Lou

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GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
Interests: GNSS precise data processing; navigation
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Prof. Dr. Chuang Shi

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School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
Interests: GNSS precise data processing; navigation; timing
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Dr. Fu Zheng

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Guest Editor

Research Institute for Frontier Science, Beihang University, Beijing 100191, China
Interests: multi-frequency GNSS PPP; real-time GNSS applications; CP-CV and PPP timing service

Dr. Xiaomin Luo

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Guest Editor

The School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Interests: GNSS ionospheric scintillation; GNSS high-precision data processing; space weather monitoring and application

Special Issue Information

Dear Colleagues,

The potential of global navigation satellite systems (GNSSs) as an efficient tool in providing precise positioning has been widely recognized. Especially, the precise point positioning (PPP) technique is receiving increasing interest due to its cost-effectiveness, global coverage and high accuracy. In addition, the emergence of multiple satellite navigation systems, including BDS, Galileo, modernized GPS and GLONASS, brings great opportunities and challenges for PPP. For instance, the additional frequency as well as the new signal of BDS-3 and Galileo enable the rapid convergence of PPP by efficient ambiguity resolution (AR). More recently, in addition to the standard point positioning, BDS, Galileo as well as QZSS have also provided satellite-based PPP service. Obviously, the development of multi-frequency multi-GNSS and their built-in PPP service has popularized the use of PPP as an efficient technique in navigation, timing as well as geoscience applications.

This Special Issue aims to explore different algorithms and applications of PPP with either GNSS built-in high-precision service or IGS high-precision product. Topics may cover anything from the classical ionospheric-free PPP to undifferenced uncombined PPP, and from the float-ambiguity PPP to fixed-ambiguity PPP. Hence, code and phase observation-specific bias estimation and correction, atmosphere augmentation PPP with multiscale networks or studies of PPP and multi-sensor integration navigation, among other issues, are welcome.

Topics of interest for this Special Issue include:

Multi-GNSS PPP;
Multi-frequency PPP;
PPP with ambiguity resolution;
PPP with atmosphere augmentation;
PPP based on BDS-3 B2b, Galileo HAS and QZSS CLAS;
PPP applications in navigation and timing;
PPP convergence;
PPP in urban environments.

Dr. Shengfeng Gu
Dr. Xiaopeng Gong
Prof. Dr. Yidong Lou
Prof. Dr. Chuang Shi
Dr. Fu Zheng
Dr. Xiaomin Luo
Guest Editors

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Keywords

multi-GNSS PPP
multi-frequency PPP
PPP with ambiguity resolution
PPP with atmosphere augmentation
PPP based on BDS-3 B2b, Galileo HAS and QZSS CLAS
PPP applications in navigation and timing
PPP convergence
PPP in urban environments

Published Papers (5 papers)

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Research

17 pages, 4959 KiB

Open AccessArticle

Improved Multi-GNSS PPP Partial Ambiguity Resolution Method Based on Two-Step Sorting Criterion

by Lin Zhao, Zhiguo Sun, Fuxin Yang, Xiaosong Liu and Jie Zhang

Remote Sens. 2023, 15(13), 3319; https://doi.org/10.3390/rs15133319 - 28 Jun 2023

Viewed by 998

Abstract

Multi-GNSS PPP partial ambiguity resolution (PAR) can improve the fixing success rate and shorten the time to first fix (TTFF). Ambiguity subset selection based on the bootstrapping success rate sorting criterion (BSSC) is widely used in PPP PAR due to its ease of computation and comprehensive evaluation of the global quality of ambiguity solutions. However, due to the influence of unmodeled errors, such as atmospheric residuals and gross errors, ambiguity parameter estimation will inevitably introduce bias. For ambiguity parameters with bias, their variance will converge incorrectly and will not accurately reflect the estimation accuracy. As a result, the selected ambiguity subset based on the BSSC becomes inaccurate, affecting the fixing success rate and TTFF. Therefore, we proposed an improved multi-GNSS PPP PAR method based on a two-step sorting criterion (TSSC). This method aims to address the influence of inaccurate variance of ambiguity parameters, particularly those with low observation quality, on the ambiguity subset selection based on the BSSC. The ambiguity subset satisfying the preset success rate threshold is selected to reduce the influence of unconverged ambiguity on the TSSC. In the first step of the sorting process, the observations whose elevation angle is below 30° or whose posterior residual falls into the IGG3 model reduction domain are clustered together. The posterior observation weight criterion (POWC) instead of the BSSC is adopted to sort ambiguities to overcome the false convergence of variance of ambiguity parameters. In the second step of the sorting process, the remaining ambiguities with reasonable variances are sorted based on the BSSC. Finally, the bottom ambiguity is removed one by one from the ambiguity subset sorted based on the two-step sorting criterion (TSSC) until the requirements of the ratio test for LAMBDA are met. The static data from 10 MGEX stations over a period of 30 days, along with urban kinematic data, were collected to validate the proposed method. Compared with the PAR based on the BSSC, the static experiments demonstrated a reduction of 8.7% and 16.8% in the TTFF and convergence time, respectively. Additionally, the positioning accuracy in the east, north, and up directions was improved by 20.1%, 17.1%, and 4.67%, respectively. Furthermore, the kinematic experiment revealed that the TTFF and convergence time decreased from 1.65 min and 10.5 min to 1.3 min and 1.8 min, respectively, with higher positioning accuracy. Full article

(This article belongs to the Special Issue Precise Point Positioning with GPS, GLONASS, BeiDou, and Galileo II)

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20 pages, 2510 KiB

Open AccessArticle

Parallel Computation of Multi-GNSS and Multi-Frequency Inter-Frequency Clock Biases and Observable-Specific Biases

by Linyang Li, Zhen Yang, Zhen Jia and Xin Li

Remote Sens. 2023, 15(7), 1953; https://doi.org/10.3390/rs15071953 - 06 Apr 2023

Cited by 1 | Viewed by 1239

Abstract

With the widespread application of GNSS, the delicate handling of biases among different systems and different frequencies is of critical importance, wherein the inter-frequency clock biases (IFCBs) and observable-specific signal biases (OSBs) should be carefully corrected. Usually, a serial approach is used to calculate these products. To accelerate the computation speed and reduce the time delay, a multicore parallel estimation strategy for IFCBs, code, and phase OSBs by utilizing task parallel library (TPL) is proposed, the parallel computations, including precise point positioning (PPP), IFCBs, and OSBs estimation, being carried out on the basis of data parallelisms and task-based asynchronous programming. Three weeks of observables from the multi-GNSS experiment campaign (MGEX) network is utilized. The result shows that the IFCB errors of GPS Block IIF and GLONASS M+ satellites are nonnegligible, in which the GLONASS M+ satellite R21 shows the largest IFCB of more than 0.60 m, while those of other systems and frequencies are marginal, and the code OSBs present excellent stability with a standard deviation (STD) of 0.10 ns for GPS and approximately 0.20 ns for other satellite systems. Besides, the phase OSBs of all systems show the stability of better than 0.10 ns, wherein the Galileo satellites show the best performance of 0.01 ns. Compared with the single-core serial computing method, the acceleration rates for IFCBs and OSBs estimation are 3.10, 5.53, 9.66, and 17.04 times higher using four, eight, sixteen, and thirty-two physical cores, respectively, through multi-core parallelized execution. Full article

(This article belongs to the Special Issue Precise Point Positioning with GPS, GLONASS, BeiDou, and Galileo II)

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17 pages, 48406 KiB

Open AccessArticle

Information Fusion for Spaceborne GNSS-R Sea Surface Height Retrieval Using Modified Residual Multimodal Deep Learning Method

by Qiang Wang, Wei Zheng, Fan Wu, Huizhong Zhu, Aigong Xu, Yifan Shen and Yelong Zhao

Remote Sens. 2023, 15(6), 1481; https://doi.org/10.3390/rs15061481 - 07 Mar 2023

Viewed by 1354

Abstract

Traditional spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) sea surface height (SSH) retrieval methods have the disadvantages of complicated error models, low retrieval accuracy, and difficulty using full DDM information. To compensate for these deficiencies while considering the heterogeneity of the input data, this paper proposes an end-to-end Modified Residual Multimodal Deep Learning (MRMDL) method that can utilize the entire range of DDM information. First, the MRMDL method is constructed based on the modified Residual Net (MResNet) and Multi-Hidden layer neural network (MHL-NN). The MResNet applicable to DDM structures is used to adaptively capture productive features of the full DDM and to convert the two-dimensional DDM data into one-dimensional numerical form. Then, the extracted features and auxiliary parameters are fused as the input data for MHL-NN to retrieve the SSH. Second, the reliability of the model is verified using SSH with tide-corrected DTU Sea Surface Height 18 (DTU18) and spaceborne radar altimeters (Jason3, HY-2C, HY-2B). Compared to the SSH provided by the DTU18 validation model and the spaceborne radar altimeter, the Pearson correlation coefficients (PCC) are 0.98 and 0.97, respectively. However, the CYGNSS satellite is not primarily employed for ocean altimetry, and the mean absolute differences (MAD) are 3.92 m and 4.32 m, respectively. Finally, the retrieval accuracy of the MRMDL method and the HALF retracking approach are compared and analyzed. Finally, this study also implements the HALF retracking algorithm to derive the SSH, and the results are compared with those computed by the MRMDL method. The MRMDL method is more accurate than the HALF retracking approach according to MAD, Root-Mean-Square Error (RMSE), and PCC, with an improvement of 35.21%, 17.25%, and 2.08%, respectively. The MRMDL method will contribute a new theoretical and methodological reference for future GNSS-R altimetry satellites with high spatiotemporal SSH retrieval. Full article

(This article belongs to the Special Issue Precise Point Positioning with GPS, GLONASS, BeiDou, and Galileo II)

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16 pages, 5067 KiB

Open AccessArticle

Long-Term Performance Evaluation of BeiDou PPP-B2b Products and Its Application in Time Service

by Qianqian He, Liang Chen, Lei Liu, Daiyan Zhao, Xiaopeng Gong, Yidong Lou and Qi Guan

Remote Sens. 2023, 15(5), 1358; https://doi.org/10.3390/rs15051358 - 28 Feb 2023

Cited by 3 | Viewed by 1371

Abstract

Precise Point Positioning (PPP) is an official service of the BeiDou Global Navigation Satellite System (BDS-3) through the PPP-B2b signal. In this paper, we mainly focus on the long-term performance evaluation of BDS-3 PPP-B2b products and their application in time service. Since the PPP-B2b product is only available in and around China area, the arcs of PPP-B2b products are about several hours. We propose to evaluate the time datum stability by using all available satellites. Then, 557 day PPP-B2b products are collected for this experiment. The results show that there are large jumps in the GPS satellite clock time datum series. However, the BDS-3 satellite clock datum stability is almost at the same level with current Space State Representation (SSR) corrections from the International Global navigation satellite system Service (IGS). The difference between PPP-B2b GPS and BDS-3 satellite clock time datum will be absorbed into the Inter System Bias (ISB) parameter. Thus, it should be specially noted that the ISB parameter cannot be estimated as constant values if users use PPP-B2b products. In addition, the accuracy of the BDS-3 satellite clock is significantly better than that of the GPS for both the Root Mean Square Error (RMSE) and standard deviation (STD). The average Signal in Space Range Errors (SISREs) is 0.22 ns and 0.13 ns for GPS and BDS-3, respectively. The one-way timing experiment shows BDS-3 timing stability is 2.9 × 10⁻¹⁴@10⁴ s. In addition, 10 baselines from 13 km to 4494 km are formed for time synchronization evaluation by using PPP-B2b products. The average RMSEs of time synchronization is from 0.46 ns to 1.58 ns and from 0.66 ns to 1.19 ns for GPS and BDS-3, respectively. As for STD, the average values are from 0.27 ns to 0.74 ns and from 0.27 ns to 0.47 ns for GPS and BDS-3, respectively. Overall, the results show that the time datum stability, accuracy, and service performance of BDS-3 PPP-B2b products has been stable over the past two years. Full article

(This article belongs to the Special Issue Precise Point Positioning with GPS, GLONASS, BeiDou, and Galileo II)

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20 pages, 4884 KiB

Open AccessArticle

Assessing the Performance of Precise Point Positioning (PPP) with the Fully Serviceable Multi-GNSS Constellations: GPS, BDS-3, and Galileo

by Zunyao Hou and Feng Zhou

Remote Sens. 2023, 15(3), 807; https://doi.org/10.3390/rs15030807 - 31 Jan 2023

Cited by 3 | Viewed by 1719

Abstract

Nowadays, both BDS-3 and Galileo can provide global positioning and navigation services. This contribution carried out a comprehensive analysis and validation of positioning performance in terms of positioning accuracy (RMS) and convergence time, which are derived from BDS-3 and Galileo precise point positioning (PPP) solutions at a global scale. Meanwhile, the comparison with GPS was demonstrated. The performance and geographical distribution of RMS and convergence time for each satellite system were analyzed. GPS outperforms the other two systems on a global scale. Galileo and BDS-3, on the other hand, only perform moderately well in certain latitude zones. The combination of dual systems related to each single system is analyzed. For the dual-system combinations, the combination of systems presents a definite advantage over Galileo and BDS-3, and this advantage is more pronounced for the kinematic PPP. For GPS, the combination with Galileo and BDS-3 has little improvement in positioning performance. For the dual-system combination based on Galileo and BDS-3, the RMS and convergence time can be improved by 50% compared with the single system. The influence of single-system kinematic PPP selection for precise products from different MGEX analysis centers on positioning performance was studied. Among the five precise products, grg products have the best positioning performance for GPS, while cod products have the best positioning performance for Galileo and BDS-3. The difference in RMS and convergence time between 2 cm and 15 min can be caused by different precise product selections. Full article

(This article belongs to the Special Issue Precise Point Positioning with GPS, GLONASS, BeiDou, and Galileo II)

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