GNSS augmentation

About: GNSS augmentation is a research topic. Over the lifetime, 2478 publications have been published within this topic receiving 28513 citations. The topic is also known as: SBAS & Satellite Based Augmentation System.

Improving the GNSS Attitude Ambiguity Success Rate with the Multivariate Constrained LAMBDA Method

Abstract: GNSS Attitude Determination is a valuable technique for the estimation of platform orientation. To achieve high accuracies on the angular estimations, the GNSS carrier phase data has to be used. These data are known to be affected by integer ambiguities, which must be correctly resolved in order to exploit the higher precision of the phase observables with respect to the GNSS code data. For a set of GNSS antennae rigidly mounted on a platform, a number of nonlinear geometrical constraints can be exploited for the purpose of strengthening the underlying observation model and subsequently improving the capacity of fixing the correct set of integer ambiguities. A multivariate constrained version of the LAMBDA method is presented and tested here.

Total system error performance of drones for an unmanned PBN concept

Abstract: The German Aerospace Center (DLR) operates small drones i.e., octocopters for research purposes at different institutions at different locations. In addition, the DLR is working on the integration of drones into unsegregated airspace in several national and international projects. One of the key elements for a safe integration of drones is the positioning capability of the air vehicle. On the one hand it is required for geofencing applications in order to create no-fly zones and on the other hand it is required to generate an airspace management for unmanned traffic. In recent years, the Performance Based Navigation (PBN) concept was introduced for manned aviation to exploit the navigation performance of modern satellite navigation and to manage the available airspace. One approach for Unmanned Aircraft System (UAS) Traffic Management (UTM) is obviously to transfer the PBN concept for drone applications. However, as drones usually use commercial off the shelf equipment that is usually not certified for aviation applications, the question is how the basic principle can be transferred. In this work, we used a commercial octocopter (MikroKopter MK Okto XL 6S12 ARF) to assess the horizontal Navigation System Error (NSE) as well as the lateral Total System Error (TSE) while using different GNSS receivers. The horizontal navigation is based on GNSS in stand-alone mode or using SBAS augmentation and a compass for directional information aid. No additional sensors like inertial measurements are used here. We are going to present the results from flight trials with two different GNSS receivers and will draw conclusions for a PBN concept for drones.

An Integrity Monitoring Technique for Multiple Failures Detection

Abstract: Within the next future, the advent of Galileo, GPS modernization and of the GNSS augmentation systems, will lead to a rapid development of GNSS receiver technologies. It is expected that the improved accuracy performance will extend the use of satellite positioning and navigation to applications where present systems do not fulfill user integrity requirements and do not allow the receiver certification. In this scenario a central role is played by the integrity receiver capability. In fact a large part of users is carrying out applications in which an error in might represent an excessive risk, in particular when human lives are involved. For these applications, the system capability of protecting the user against system failure is of primary importance. The main example is given by aeronautical applications where at present the fulfillment of integrity requirements during approaches of type CAT I (and higher) has still to be reached. In this context, it is essential for the user to take advantage of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In fact, although regional integrity is provided by space-based augmentation systems (SBAS) like EGNOS, WAAS and MSAS and global integrity will be transmitted by the European Galileo satellite navigation system in the near future, RAIM is the only technique able to monitor receiver local errors. Since it is located at the end of the integrity processing chain, its role is essential in the integrity determination process. It is also highlighted that present RAIM techniques have limitations, which in particular jeopardize the possibility to certificate satellite navigation receiver as sole or stand alone positioning platform in aeronautical applications. The main limitation is represented by the fact that all present RAIM techniques protect users only against one single failure affecting a particular satellite range measurement. Multiple failure events are usually assumed to have a very low probability of occurrence. But since in safety of life applications the continuity and availability requirements in terms of probability of missed detection are very strict, the multiple failure events need more attention and cannot be disregarded anymore by RAIM techniques. This paper presents an investigation on present RAIM technique and their performance with respect to multiple failures. Furthermore it presents a technique able to overcome the present integrity monitoring limitations and to protect the user receiver in case of multiple failures.

GNSS for Enhanced Odometry: The GRAIL-2 results

Abstract: GRAIL-2 is the evolution of the GRAIL project (GNSS introduction in the RAIL Sector), a project funded by the GSA (GNSS Supervisor Authority) with the aim of facilitating the introduction of GNSS (Galileo and EGNOS) in the Rail sector GRAIL-2 takes over it predecessor focusing on the development of a GNSS based Enhanced Odometer with high integrity and safety level in a context of High Speed Lines (HSL) The purpose of a GNSS based odometer is to integrate and/or replace the traditional odometric systems currently used in the ETCS environment (tachometers, INS, Doppler radar etc) GRAIL-2 inherits the know-how acquired by GRAIL improving the accuracy of the computed Position-Velocity-Acceleration solution by means of an advanced data fusion algorithm The safety level is guaranteed introducing RAIM and Protection Level computation algorithms The purpose of this paper is to describe the results obtained analyzing the preliminary data captured on the train

Landslide Detection and Mapping Based on SBAS-InSAR and PS-InSAR: A Case Study in Gongjue County, Tibet, China

Abstract: The rock mass along the Jinsha River is relatively broken under complex geological action. Many ancient landslides were distributed along the Jinsha River in Gongjue County, which is very dangerous under the action of gravity, tectonic stress and river erosion. Efficient and accurate identification and monitoring of landslides is important for disaster monitoring and early warning. Interferometric synthetic aperture radar (InSAR) technology has been proved to be an effective technology for landslide hazard identification and mapping. However, great uncertainty inevitably exists due to the single deformation observation method, resulting in wrong judgment during the process of landslide detection. Therefore, to address the uncertainties arising from single observations, a cross-comparison method is put forward using SBAS-InSAR (small baseline subset InSAR) and PS-InSAR (permanent scatterers InSAR) technology. Comparative analysis of the spatial complementarity of interference points and temporal deformation refined the deformation characteristics and verified the reliability of the InSAR results, aiding in the comprehensive identification and further mapping of landslides. Landslides along the Jinsha River in Gongjue County were studied in this paper. Firstly, 14 landslides with a total area of 20 km2 were identified by using two time-series InSAR methods. Then, the deformation characteristics of these landslides were validated by UAV (unmanned aerial vehicle) images, multiresource remote sensing data and field investigation. Further, the precipitation data were introduced to analyze the temporal deformation characteristics of two large landslides. Lastly, the influence of fault activity on landslide formation is further discussed. Our results demonstrate that the cross-comparison of the time-series InSAR method can effectively verify the accuracy of landslide identification.