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1
Content available A PPP baseline approach for bridge passing
EN
Global Navigation Satellite Systems (GNSS) are increasingly used as the main source of Positioning, Navigation and Timing (PNT) information for inland water navigation. In order to enable automated driving and facilitate driver assistant functions, it becomes of crucial importance to ensure high reliability and accuracy of the GNSS-based navigation solution, especially in challenging environments. One challenging phase of inland waterway navigation is bridge passing which leads to non-line-of-sight (NLOS) effects such as multipath and loss of tracking. This work presents a Precise Point Positioning (PPP) based algorithm in a two-antenna system where one antenna is at the bow and the other is at the stern. Additionally, gyroscope data from an IMU is used. In contrast to a separated position calculation of the two antennas, only one antenna position is estimated and the other is derived from the baseline between the antennas. This allows for accurate positioning even if one antenna does not receive any GNSS measurements. The presented scheme is evaluated using real measurement data from an inland water scenario with multiple bridges. In comparison with a standard PPP scheme as well as an RTK algorithm, the presented approach shows clear advantages in challenging scenarios.
EN
Galileo High Accuracy Service (HAS) became available in January 2023. As declared, in its final operational capability, it should be able to provide to users the Precise Point Positioning (PPP) at horizontal accuracy level better than 20 cm in real-time with 95% confidence globally. At the moment Galileo HAS works in its initial phase of operation with some limitations regarding its availability, convergence time and accuracy but gives the chance to observe the performance of positioning tool at the accuracy level which was available before by using differential measurement only. Galileo HAS PPP, free of charge and based only on satellite signals delivered by nominal Galileo constellation is unique in its kind between various GNSS positioning modes. This article presents the results of first, preliminary tests on Galileo HAS performance conducted in July 2023 in Gdynia, Poland. The field tests were conducted with Galileo HAS capable receiver in static conditions and focused on the verification the declared service performance in the real positioning scenarios. Additionally, the Galileo HAS PPP performance was compared with the simultaneous performance of other GNSS positioning methods such as EGNOS, DGPS, dual frequency GPS+Galileo or dual frequency GPS and dual frequency Galileo. This first experiences with Galileo HAS positioning should show all potential users what performance level can be achieved with this new, unique in its kind GNSS positioning method at the present state of its implementation.
PL
Galileo High Accuracy Service (HAS) stał się dostępny w styczniu roku 2023. Tak jak zadeklarowano, po osiągnięciu finalnej fazy operacyjnej serwisu powinien on zapewnić użytkownikom globalną możliwość realizacji trybu Precise Point Positioning (PPP) z dokładnością wyznaczania pozycji na płaszczyźnie na poziomie lepszym niż 20 cm w czasie rzeczywistym i na 95% poziomie ufności. Aktualnie serwis Galileo HAS pracuje w początkowej fazie operacyjnej z pewnymi ograniczeniami dotyczącymi dostępności, czasu inicjalizacji oraz dokładności, ale pozwala już na uzyskiwanie dokładności wyznaczeń pozycyjnych na poziomie dokładności, który wcześniej był osiągalny tylko z wykorzystaniem metod różnicowych GNSS. Ponadto, serwis Galileo HAS PPP jest serwisem ogólnodostępnym i wykorzystującym tylko nominalne satelity nawigacyjne systemu Galileo, co czyni go unikalnym wśród aktualnie dostępnych metod GNSS. W artykule zaprezentowano wyniki pierwszych, wstępnych eksperymentów oceniających parametry operacyjne serwisu Galileo HAS przeprowadzonych w Gdyni w lipcu 2023 r. Testy serwisu przeprowadzono w warunkach statycznych z wykorzystaniem odbiornika realizującego wyznaczenia pozycyjne z zastosowaniem sygnału Galileo HAS. Pomiary miały na celu weryfikację deklarowanych parametrów dokładnościowych i dostępnościowych serwisu w rzeczywistych warunkach pomiarowych. Dodatkowo, obserwowane parametry serwisu Galileo HAS PPP zostały porównane z rejestrowanymi równolegle wynikami wyznaczeń pozycyjnych uzyskiwanych innymi metodami GNSS, takimi jak: EGNOS, DGPS, dwuczęstotliwościowe pomiary GPS+Galileo oraz dwuczęstotliwościowy GPS i dwuczęstotliwościowy Galileo. Przedstawione w artykule wyniki pierwszych doświadczeń z wykorzystaniem serwisu Galileo HAS pokazują wszystkim potencjalnym użytkownikom, czego mogą się spodziewać, wykorzystując w procesie wyznaczania pozycji tę nową i unikalną w swoim rodzaju metodę pozycyjną GNSS na jej aktualnym etapie wdrażania.
EN
Solar variations modify a layer of the Earth’s upper atmosphere known as the ionosphere. This is of particular concern for the aviation sector because of the way its communications and navigation systems can be affected. At the same time, one of the most complex atmospheric effects is the response of ionospheric regions to geomagnetic storms. The ionospheric response during the same storm can vary in time in different locations, which can introduce significant errors/displacement (meters) in single-frequency relative GNSS positioning (DGNSS technology). The residual effect can be somewhat mitigated by using dual- or multi-frequency GNSS, but dual frequency is not a guarantee against degradation of relative observations results, especially during significant geomagnetic storms. In this regard, PPP absolute positioning technology can be effective. However, another atmospheric effect - ionospheric scintillation can have a significant impact on the accuracy of both GNSS positioning approaches. The main goal of this study was to analyze the effect of second-order ionospheric delay during geomagnetic storms and ionospheric scintillations on GNSS positioning using the PPP method. GNSS data corrected and uncorrected for higher-order ionospheric delay, respectively, were processed by the static PPP-AR method using the PRIDE-PPPAR ver.2.2.6 software for the selected periods of geomagnetic storms. From the analysis of the influence of second-order ionospheric errors, it follows that their values can reach almost 4 cm for first-frequency signals under different states of ionospheric disturbances for the GPS constellation and almost an order of magnitude less for the GNSS quadroconstellation. The appearance of stronger geomagnetic storms increases the second-order ionospheric errors by several millimeters.
PL
Wahania aktywności Słońca modyfikują górną warstwę atmosfery Ziemi, zwaną jonosferą. Jest to szczególnie niepokojące dla sektora lotnictwa ze względu na wpływ, jaki może to mieć na jego systemy łączności i nawigacji. Jednocześnie jednym z najbardziej złożonych efektów atmosferycznych jest reakcja obszarów jonosfery na burze geomagnetyczne. Reakcja jonosfery podczas tej samej burzy może zmieniać się w czasie w różnych lokalizacjach, co może powodować znaczne błędy/ przemieszczenia (rzędu kilku metrów) we względnym pozycjonowaniu GNSS przy jednej częstotliwości (technologia DGNSS). Efekt resztkowy można w pewnym stopniu złagodzić, stosując dwu- lub wieloczęstotliwościowy GNSS, jednak podwójna częstotliwość nie gwarantuje zapobiegania degradacji wyników względnych obserwacji, szczególnie podczas silnych burz geomagnetycznych. Pod tym względem skuteczna może być technologia pozycjonowania absolutnego PPP. Jednak inny efekt atmosferyczny - scyntylacja jonosferyczna może mieć znaczący wpływ na dokładność obu podejść do pozycjonowania GNSS. Głównym celem pracy była analiza wpływu opóźnienia jonosferycznego drugiego rzędu podczas burz geomagnetycznych i scyntylacji jonosferycznych na pozycjonowanie GNSS metodą PPP. Dane GNSS skorygowane i nieskorygowane pod kątem opóźnienia jonosferycznego wyższego rzędu przetworzono statyczną metodą PPP-AR z wykorzystaniem oprogramowania PRIDE-PPPAR wersja 2.2.6 dla wybranych okresów burz geomagnetycznych. Z analizy wpływu błędów jonosferycznych drugiego rzędu wynika, że ich wartości mogą sięgać prawie 4 cm dla sygnałów pierwszej częstotliwości w różnych stanach zaburzeń jonosferycznych dla konstelacji GPS i prawie o rząd wielkości mniej dla kwadrokonstelacji GNSS. Pojawienie się silniejszych burz geomagnetycznych zwiększa błędy jonosferyczne drugiego rzędu o kilka milimetrów.
EN
Bridge passing and passing waterway locks are two of the most challenging phases for inland vessel navigation. In order to be able to automate these critical phases very precise and reliable position, navigation and timing (PNT) information are required. Here, the application of code-based positioning using signals of Global Navigation Satellite Systems (GNSS) is not sufficient anymore and phase-based positioning needs to be applied. Due to the larger coverage area and the reduction of the amount of correction data Precise Point Positioning (PPP) has significant advantages compared to the established Real Time Kinematic (RTK) positioning. PPP is seen as the key enabler for highly automatic driving for both road and inland waterway transport. This paper gives an overview of the current status of the developments of the PPP algorithm, which should finally be applied in advanced driver assistant functions. For the final application State Space Representation (SSR) correction data from SAPOS (Satellitenpositionierungsdienst der deutschen Landesvermessung) will be used, which will be transmitted over VDES (VHF Data Exchange System), the next generation AIS.
EN
The precise point positioning (PPP) method has become more popular due to powerful online global navigation satellite system (GNSS) data processing services, such as the Canadian Spatial Reference System-PPP (CSRS-PPP). At the end of 2020, the CSRS-PPP service launched the ambiguity resolution (AR) feature for global positioning system (GPS) satellites. More reliable results are obtained with AR compared to the results with traditional ambiguity-float PPP. In this study, the performance of the modernized CSRS-PPP was comparatively assessed in terms of static positioning and zenith total delay (ZTD) estimation. Data for 1 month in the year 2019 obtained from 47 international GNSS service (IGS) stations were processed before and after modernization of the CSRS-PPP. The processes were conducted for GPS and GPS + GLONASS (GLObalnaya NAvigatsionnaya Sputnikovaya Sistema) satellite combinations. Besides, the results were analyzed in terms of accuracy and convergence time. According to the solutions, the AR feature of the CSRS-PPP improved the accuracy by about 50% in the east component for GPS + GLONASS configuration. The rootmean-square error (RMSE) of the ZTD difference between modernized CSRS-PPP service and IGS final troposphere product is 5.8 mm for the GPS-only case.
EN
In addition to Global Positioning System (GPS) constellation, the number of Global Navigation Satellite System (GLONASS) satellites is increasing; it is now possible to evaluate and analyze the position accuracy with both the GPS and GLONASS constellation. In this article, statistical analysis of static precise point positioning (PPP) using GPS-only, GLONASS-only, and combined GPS/GLONASS modes is evaluated. Observational data of 10 whole days from 10 International GNSS Service (IGS) stations are used for analysis. Position accuracy in east, north, up components, and carrier phase/code residuals is analyzed. Multi-GNSS PPP open-source package is used for the PPP performance analysis. The analysis also provides the GNSS researchers the understanding of the observational data processing algorithm. Calculation statistics reveal that standard deviation (STD) of horizontal component is 3.83, 13.80, and 3.33 cm for GPS-only, GLONASS-only, and combined GPS/GLONASS PPP solutions, respectively. Combined GPS/GLONASS PPP achieves better positioning accuracy in horizontal and three-dimensional (3D) accuracy compared with GPSonly and GLONASS-only PPP solutions. The results of the calculation show that combined GPS/GLONASS PPP improves, on an average, horizontal accuracy by 12.11% and 60.33% and 3D positioning accuracy by 10.39% and 66.78% compared with GPS-only and GLONASS-only solutions, respectively. In addition, the results also demonstrate that GPSonly solutions show an improvement of 54.23% and 62.54% compared with GLONASS-only PPP mode in horizontal and 3D components, respectively. Moreover, residuals of GLONASS ionosphere-free code observations are larger than the GPS code residuals. However, phase residuals of GPS and GLONASS phase observations are of the same magnitude.
7
Content available remote Efficiency of using GNSS-PPP for digital elevation model (DEM) production
EN
In the developing countries, cost-effective observation techniques are very important for earthwork estimation, map production, geographic information systems, and hydrographic surveying. One of the most cost-effective techniques is Precise Point Positioning (PPP); it is a Global Navigation Satellite Systems (GNSS) positioning technique to compute precise positions using only a single GNSS receiver. This study aims to evaluate the efficiency of using Global Positioning System (GPS) and GPS/ Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) post-processed kinematic PPP solution for digital elevation model (DEM) production, which is used in earthwork estimation. For this purpose, a kinematic trajectory has been observed in New Aswan City in an open sky area using dual-frequency GNSS receivers. The results showed that, in case of using GPS/GLONASS PPP solution to estimate volumes, the error in earthwork volume estimation varies between 0.07% and 0.16% according to gridding level. On the other hand, the error in volume estimation from GPS PPP solution varies between 0.40% and 0.99%.
8
EN
This study assesses the precision of zenith tropospheric delay (ZTD) obtained through triple-constellation global navigation satellite system (GNSS) precise point positioning (PPP). Various ZTD estimates are obtained as by-products from GPS-only, GPS/Galileo, GPS/BeiDou, and triple-constellation GPS/Galileo/BeiDou PPP solutions. Triple-constellation GNSS observations from a number of globally distributed reference stations are processed over a period of seven days in order to investigate the daily performance of the ZTD estimates. The estimated ZTDs are then validated by comparing them with the International GNSS Service (IGS) tropospheric products and the University of New Brunswick (UNB3m) model counterparts. It is shown that the ZTD estimates agree with the IGS counterparts with a maximum standard deviation (STD) of 2.4 cm. It is also shown that the precision of estimated ZTD from the GPS/Galileo and GPS/Galileo/BeiDou PPP solutions is improved by about 4.5 and 14%, respectively, with respect to the GPS-only PPP solution. Moreover, it is found that the estimated ZTD agrees with the UNB3m model with a maximum STD of 3.1 cm. Furthermore, the GPS/Galileo and GPS/Galileo/BeiDou PPP enhance the precision of the ZTD estimates by about 6.5 and 10%, respectively, in comparison with the GPS-only PPP solution.
EN
The accuracy and reliability of Kalman filter are easily affected by the gross errors in observations. Although robust Kalman filter based on equivalent weight function models can reduce the impact of gross errors on filtering results, the conventional equivalent weight function models are more suitable for the observations with the same noise level. For Precise Point Positioning (PPP) with multiple types of observations that have different measuring accuracy and noise levels, the filtering results obtained with conventional robust equivalent weight function models are not the best ones. For this problem, a classification robust equivalent weight function model based on the t-inspection statistics is proposed, which has better performance than the conventional equivalent weight function models in the case of no more than one gross error in a certain type of observations. However, in the case of multiple gross errors in a certain type of observations, the performance of the conventional robust Kalman filter based on the two kinds of equivalent weight function models are barely satisfactory due to the interaction between gross errors. To address this problem, an improved classification robust Kalman filtering method is further proposed in this paper. To verify and evaluate the performance of the proposed method, simulation tests were carried out based on the GPS/BDS data and their results were compared with those obtained with the conventional robust Kalman filtering method. The results show that the improved classification robust Kalman filtering method can effectively reduce the impact of multiple gross errors on the positioning results and significantly improve the positioning accuracy and reliability of PPP.
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