Helmert Variance Component Estimation for Multi-GNSS Relative Positioning

The Multi-constellation Global Navigation Satellite System (Multi-GNSS) has become the standard implementation of high accuracy positioning and navigation applications. It is well known that the noise of code and phase measurements depend on GNSS constellation. Then, Helmert variance component estimation (HVCE) is usually used to adjust the contributions of di¿erent GNSS constellations by determining their individual variances of unit weight. However, HVCE requires a heavy computation load. In this study, the HVCE posterior weighting was employed to carry out a kinematic relative Multi-GNSS positioning experiment with six short-baselines from day of year (DoY) 171 to 200 in 2019. As a result, the HVCE posterior weighting strategy improved Multi-GNSS positioning accuracy by 20.5%, 15.7% and 13.2% ineast-north-up(ENU) components, compared to an elevation-dependent (ED) priori weighting strategy. We observed that the weight proportion of both code and phase observations for each GNSS constellation were consistent during the entire 30 days, which indicates that the weight proportions of both code and phase observations are stable over a long period of time. It was also found that the quality of a phase observation is almost equivalent in each baseline and GNSS constellation, whereas that of a code observation is different. In order to reduce the time consumption off the HVCE method without sacrificing positioning accuracy, the stable variances of unit weights of both phase and code observations obtained over 30 days were averaged and then frozen as a priori information in the positioning experiment. The result demonstrated similar ENU improvements of 20.0%, 14.1% and 11.1% with respect to the ED method but saving 88% of the computation time of the HCVE strategy. Our study concludes with the observations that the frozen variances of unit weight (FVUW) could be applied to the positioning experiment for the next 30 days, that is, from DoY 201 to 230 in 2019, improving the positioning ENU accuracy of the ED method by 18.1%, 13.2% and 10.6%, indicating the effectiveness of the FVUW.Peer ReviewedPostprint (published version

Multi-GNSS positioning for landslide monitoring: A case study at the Recica landslide

Global Navigation Satellite System (GNSS) positioning has characteristics of simple operation, high efficiency and high precision technique for landslide surface monitoring. In recent years, finalization of modern GNSS systems Galileo and BeiDou has brought a possibility of multi-GNSS positioning. The paper focuses on evaluation of possible benefits of multi-GNSS constellations in landslide monitoring. While simulating observational conditions of selected Recica landslide in the Czech Republic, one-month data from well-established permanent GNSS reference stations were processed. Besides various constellation combinations, differential and Precise Point Positioning techniques, observation data lengths and observation sampling intervals were evaluated. Based on the results, using a combination of GPS and GLONASS, or GPS, GLONASS and Galileo systems can be recommended, together with a static differential technique and observation periods for data collection exceeding eight hours. In the last step, data from GNSS repetitive campaigns realized at the Recica landslide during two years were processed with optimal setup and obtained displacement results were compared to standard geotechnical measurements.Web of Science19327025

Application of Multi-GNSS Positioning in Landslide Surface Deformation Monitoring

With a modernization of legacy GPS and GLONASS systems, as well as with a finalization of the new European Galileo and Chinese BeiDou systems, about 120 navigation satellites for Global Navigation Satellite System (GNSS) users around the world are available presently. Usage of multi-GNSS constellations has therefore become an important research topic in recent years, including the area of landslide monitoring. The main goal of this dissertation thesis was to analyze and study positioning accuracy and performance of different satellite systems combinations with focus on finding the optimal strategy for multi-GNSS data collection and processing in landslide monitoring applications. Five stabilized monitoring points allowing repetitive GNSS observation campaigns were established at the selected Recica landslide in the Czech Republic. Quality of current multi-GNSS precise products provided by different analysis centers (ACs) was evaluated to allow a selection of the optimal one. Although no substantial differences were found, products provided by GeoForschungsZentrum (GFZ) and Center for Orbit Determination in Europe (CODE) can be recommended in overall. Consequently, positioning accuracy provided by various constellation combinations was analyzed by using data from well-established GNSS reference stations while simulating observation conditions of the Recica landslide. The best results were obtained when processing signals from a combination of GPS and GLONASS, or GPS, GLONASS and Galileo systems, with a static relative differential technique and observation periods for data collection exceeding eight hours. Finally, data from GNSS repetitive campaigns realized at the Recica landslide during two years were processed with optimal setup and obtained displacement results were compared to standard geotechnical measurements. A horizontal displacement with an annual velocity of about 3 cm in the horizontal direction was found for three monitoring points while the other two points were more stable.With a modernization of legacy GPS and GLONASS systems, as well as with a finalization of the new European Galileo and Chinese BeiDou systems, about 120 navigation satellites for Global Navigation Satellite System (GNSS) users around the world are available presently. Usage of multi-GNSS constellations has therefore become an important research topic in recent years, including the area of landslide monitoring. The main goal of this dissertation thesis was to analyze and study positioning accuracy and performance of different satellite systems combinations with focus on finding the optimal strategy for multi-GNSS data collection and processing in landslide monitoring applications. Five stabilized monitoring points allowing repetitive GNSS observation campaigns were established at the selected Recica landslide in the Czech Republic. Quality of current multi-GNSS precise products provided by different analysis centers (ACs) was evaluated to allow a selection of the optimal one. Although no substantial differences were found, products provided by GeoForschungsZentrum (GFZ) and Center for Orbit Determination in Europe (CODE) can be recommended in overall. Consequently, positioning accuracy provided by various constellation combinations was analyzed by using data from well-established GNSS reference stations while simulating observation conditions of the Recica landslide. The best results were obtained when processing signals from a combination of GPS and GLONASS, or GPS, GLONASS and Galileo systems, with a static relative differential technique and observation periods for data collection exceeding eight hours. Finally, data from GNSS repetitive campaigns realized at the Recica landslide during two years were processed with optimal setup and obtained displacement results were compared to standard geotechnical measurements. A horizontal displacement with an annual velocity of about 3 cm in the horizontal direction was found for three monitoring points while the other two points were more stable.548 - Katedra geoinformatikyvyhově

A New Azimuth-Dependent Elevation Weight (ADEW) Model for Real-Time Deformation Monitoring in Complex Environment by Multi-GNSS

Global navigation satellite systems (GNSS) have provided an excellent way to monitor micro-deformation in real-time. However, at local sites where landslides frequently occur, the environment can include complex surroundings with mountains, dense vegetation, and human settlements, which can severely degrade the accuracy of positioning with the GNSS technique. In this study, we propose an azimuth-dependent elevation weight (ADEW) model using an azimuth-dependent elevation mask (ADEM) to reduce the effects of multipath errors and improve the accuracy of real-time deformation monitoring in such environments. We developed an adaptive fixed-elevation mask to serve as the outlier of low precision observations at lower elevations for the ADEM, and then, we applied the weighted phase observations into the mitigation process for the effects of multipath errors. The real numerical results indicate that the ADEM model performs better than the conventional model, and the average improvements were 18.91% and 34.93% in the horizontal and vertical direction, respectively. The ADEW model further improved upon the ADEM model results by an additional 21.9% and 29.8% in the horizontal and vertical direction, respectively. Therefore, we propose that the ADEW model can significantly mitigate the effects of multipath errors and improve the accuracy of micro-deformation monitoring via GNSS receivers

A New Azimuth-Dependent Elevation Weight (ADEW) Model for Real-Time Deformation Monitoring in Complex Environment by Multi-GNSS

Global navigation satellite systems (GNSS) have provided an excellent way to monitor micro-deformation in real-time. However, at local sites where landslides frequently occur, the environment can include complex surroundings with mountains, dense vegetation, and human settlements, which can severely degrade the accuracy of positioning with the GNSS technique. In this study, we propose an azimuth-dependent elevation weight (ADEW) model using an azimuth-dependent elevation mask (ADEM) to reduce the effects of multipath errors and improve the accuracy of real-time deformation monitoring in such environments. We developed an adaptive fixed-elevation mask to serve as the outlier of low precision observations at lower elevations for the ADEM, and then, we applied the weighted phase observations into the mitigation process for the effects of multipath errors. The real numerical results indicate that the ADEM model performs better than the conventional model, and the average improvements were 18.91% and 34.93% in the horizontal and vertical direction, respectively. The ADEW model further improved upon the ADEM model results by an additional 21.9% and 29.8% in the horizontal and vertical direction, respectively. Therefore, we propose that the ADEW model can significantly mitigate the effects of multipath errors and improve the accuracy of micro-deformation monitoring via GNSS receivers