Author
Weijing Qu
Bio: Weijing Qu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: GLONASS & GNSS applications. The author has an hindex of 2, co-authored 3 publications receiving 44 citations.
Papers
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TL;DR: A simplified and unified model for multi-GNSS PPP is developed, where ISB parameter does not need to be estimated and observations from different GNSS systems are treated in a unified way.
54 citations
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TL;DR: Investigation of the contribution of CME in GPS filtered residuals time series shows the Root Mean Squares of GPS time series are reduced by applying of the mass loading corrections in CME.
Abstract: Common mode error (CME) in Chuandian region of China is derived from 6-year continuous GPS time series and is identified by principal component analysis (PCA) method. It is revealed that the temporal behavior of the CME is not purely random, and contains unmodeled signals such as nonseasonal mass loadings. Its spatial distribution is quite uniform for all GPS sites in the region, and the first principal component, uniformly distributed in the region, has a spatial response of more than 70%. To further explore the potential contributors of CME, daily atmospheric mass loading and soil moisture mass loading effects are evaluated. Our results show that ~15% of CME can be explained by these daily surface mass loadings. The power spectral analysis is used to assess the CME. After removing atmospheric and soil moisture loadings from the CME, the power of the CME reduces in a wide range of frequencies. We also investigate the contribution of CME in GPS filtered residuals time series and it shows the Root Mean Squares (RMSs) of GPS time series are reduced by applying of the mass loading corrections in CME. These comparison results demonstrate that daily atmosphere pressure and the soil moisture mass loadings are a part of contributors to the CME in Chuandian region of China.
9 citations
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TL;DR: In this article, the authors used the continuous site position time series of International GNSS Service (IGS) from 1995 to 2020 as a benchmark to investigate the characteristics of the three frames.
Abstract: A terrestrial reference frame (TRF) is derived based on historical geodetic data and is normally updated every 5–6 years. The three most recent International Terrestrial Reference System (ITRS) realizations, ITRF2014, DTRF2014, and JTRF2014, were determined with different strategies, which has resulted in different signals in the reference frame parameters. In this paper, we used the continuous site position time series of International GNSS Service (IGS) from 1995 to 2020 as a benchmark to investigate the characteristics of the three frames. In the comparison, the ITRS realizations were divided into the determination and prediction sections, where the site coordinates of the TRFs were extrapolated in the prediction period. The results indicated that the orientation and scale parameters of the ITRF2014, and the IGS solutions showed excellent agreement during the determination period of ITRF2014, while, during the prediction period, the orientation parameter diverged from IGS with rates of 11.9, 5.5, and 8.4 μas/yr, and the scale degraded with a rate of −0.038 ppb/yr. The consistency of the origin parameters between the DTRF2014 and the IGS solutions during the two periods changed from 0.07, 0.11, and −0.15 mm/yr to −0.17, −0.18, and −0.12 mm/yr; the consistency of orientation parameters from −3.6, −1.9, and 2.9 μas/yr to 15.9, −2.3, and 13.2 μas/yr; and the consistency of scale from 0.007 to −0.005 ppb/yr. In the comparison between the JTRF2014 and IGS solutions, annual signals in the origin differences were 1.5, 3.0, and 2.4 mm in the X, Y, and Z components, respectively, and the temporal variation trends in different periods disagreed with their long-term trends. Obvious trend switches in the rotation parameters were also observable, and the complex temporal variation characteristics of the scale offsets may be related to the scale definition strategy applied in different TRFs.
2 citations
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TL;DR: A GPS + BDS fractional cycle bias (FCB) estimation method and a PPP AR model developed using integrated GPS and BDS observations that outperforms single-system PPPAR in terms of convergence time and position accuracy are verified.
Abstract: This paper focuses on the contribution of the global positioning system (GPS) and BeiDou navigation satellite system (BDS) observations to precise point positioning (PPP) ambiguity resolution (AR). A GPS + BDS fractional cycle bias (FCB) estimation method and a PPP AR model were developed using integrated GPS and BDS observations. For FCB estimation, the GPS + BDS combined PPP float solutions of the globally distributed IGS MGEX were first performed. When integrating GPS observations, the BDS ambiguities can be precisely estimated with less than four tracked BDS satellites. The FCBs of both GPS and BDS satellites can then be estimated from these precise ambiguities. For the GPS + BDS combined AR, one GPS and one BDS IGSO or MEO satellite were first chosen as the reference satellite for GPS and BDS, respectively, to form inner-system single-differenced ambiguities. The single-differenced GPS and BDS ambiguities were then fused by partial ambiguity resolution to increase the possibility of fixing a subset of decorrelated ambiguities with high confidence. To verify the correctness of the FCB estimation and the effectiveness of the GPS + BDS PPP AR, data recorded from about 75 IGS MGEX stations during the period of DOY 123-151 (May 3 to May 31) in 2015 were used for validation. Data were processed with three strategies: BDS-only AR, GPS-only AR and GPS + BDS AR. Numerous experimental results show that the time to first fix (TTFF) is longer than 6 h for the BDS AR in general and that the fixing rate is usually less than 35 % for both static and kinematic PPP. An average TTFF of 21.7 min and 33.6 min together with a fixing rate of 98.6 and 97.0 % in static and kinematic PPP, respectively, can be achieved for GPS-only ambiguity fixing. For the combined GPS + BDS AR, the average TTFF can be shortened to 16.9 min and 24.6 min and the fixing rate can be increased to 99.5 and 99.0 % in static and kinematic PPP, respectively. Results also show that GPS + BDS PPP AR outperforms single-system PPP AR in terms of convergence time and position accuracy.
99 citations
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TL;DR: A review of the research conducted until present on the subject of Global Navigation Satellite System (GNSS) hardware-induced phase and code biases is provided and illustrates how satellite phase biases inhibit the resolution of the phase ambiguity to an integer in PPP, while receiver phase biases affect multi-GNSS positioning.
Abstract: A review of the research conducted until present on the subject of Global Navigation Satellite System (GNSS) hardware-induced phase and code biases is here provided. Biases in GNSS positioning occu ...
94 citations
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TL;DR: An overview of the current performance of PPP is provided as well as attempt to address some of the common misconceptions of this positioning technique—considered by many as the future of satellite positioning and navigation.
Abstract: Within the last decade, GNSS Precise Point Positioning (PPP) has generated unprecedented interest among the GNSS community and is being used for a number of scientific and commercial applications today. Similar to the conventional relative positioning technique, PPP could provide positioning solutions at centimeter-level precision by making use of the precise carrier phase measurements and high-accuracy satellite orbits and clock corrections provided by, for example, the International GNSS Service. The PPP technique is attractive as it is computationally efficient; it eliminates the need for simultaneous observations at both the reference and rover receivers; it also eliminates the needs for the rover receiver to operate within the vicinity of the reference receiver; and it provides homogenous positioning quality within a consistent global frame anywhere in the world with a single GNSS receiver. Although PPP has definite advantages for many applications, its merits and widespread adoption are significantly limited by the long convergence time, which restricts the use of the PPP technique for many real-time GNSS applications. We provide an overview of the current performance of PPP as well as attempt to address some of the common misconceptions of this positioning technique--considered by many as the future of satellite positioning and navigation. Given the upcoming modernization and deployment of GNSS satellites over the next few years, it would be appropriate to address the potential impacts of these signals and constellations on the future prospect of PPP.
89 citations
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TL;DR: An effective uncalibrated phase delay (UPD) estimation and AR strategy which is based on a raw PPP model and shows that compared with the ambiguity-float solution, the performance in terms of convergence time and positioning biases can be significantly improved by AR.
Abstract: All BeiDou navigation satellite system (BDS) satellites are transmitting signals on three frequencies, which brings new opportunity and challenges for high-accuracy precise point positioning (PPP) with ambiguity resolution (AR). This paper proposes an effective uncalibrated phase delay (UPD) estimation and AR strategy which is based on a raw PPP model. First, triple-frequency raw PPP models are developed. The observation model and stochastic model are designed and extended to accommodate the third frequency. Then, the UPD is parameterized in raw frequency form while estimating with the high-precision and low-noise integer linear combination of float ambiguity which are derived by ambiguity decorrelation. Third, with UPD corrected, the LAMBDA method is used for resolving full or partial ambiguities which can be fixed. This method can be easily and flexibly extended for dual-, triple- or even more frequency. To verify the effectiveness and performance of triple-frequency PPP AR, tests with real BDS data from 90 stations lasting for 21 days were performed in static mode. Data were processed with three strategies: BDS triple-frequency ambiguity-float PPP, BDS triple-frequency PPP with dual-frequency (B1/B2) and three-frequency AR, respectively. Numerous experiment results showed that compared with the ambiguity-float solution, the performance in terms of convergence time and positioning biases can be significantly improved by AR. Among three groups of solutions, the triple-frequency PPP AR achieved the best performance. Compared with dual-frequency AR, additional the third frequency could apparently improve the position estimations during the initialization phase and under constraint environments when the dual-frequency PPP AR is limited by few satellite numbers.
80 citations
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TL;DR: Generally, the positioning performance of PPP in terms of convergence time and positioning accuracy with the final products from CODE, CNES, and WHU is comparable among the three ISB handling schemes, however, estimating ISBs as random walk process or white noise process outperforms that as the random constant when using the GFZ products.
Abstract: The focus of this study is on proper modeling of the dynamics for inter-system biases (ISBs) in multi-constellation Global Navigation Satellite System (GNSS) precise point positioning (PPP) processing. First, the theoretical derivation demonstrates that the ISBs originate from not only the receiver-dependent hardware delay differences among different GNSSs but also the receiver-independent time differences caused by the different clock datum constraints among different GNSS satellite clock products. Afterward, a comprehensive evaluation of the influence of ISB stochastic modeling on undifferenced and uncombined PPP performance is conducted, i.e., random constant, random walk process, and white noise process are considered. We use data based on a 1-month period (September 2017) Multi-GNSS Experiment (MGEX) precise orbit and clock products from four analysis centers (CODE, GFZ, CNES, and WHU) and 160 MGEX tracking stations. The results demonstrate that generally, the positioning performance of PPP in terms of convergence time and positioning accuracy with the final products from CODE, CNES, and WHU is comparable among the three ISB handling schemes. However, estimating ISBs as random walk process or white noise process outperforms that as the random constant when using the GFZ products. These results indicate that the traditional estimation of ISBs as the random constant may not always be reasonable in multi-GNSS PPP processing. To achieve more reliable positioning results, it is highly recommended to consider the ISBs as random walk process or white noise process in multi-GNSS PPP processing.
77 citations