GNSS augmentation | EPFL Graph Search

Augmentation of a global navigation satellite system (GNSS) is a method of improving the navigation system's attributes, such as precision, reliability, and availability, through the integration of external information into the calculation process. There are many such systems in place, and they are generally named or described based on how the GNSS sensor receives the external information. Some systems transmit additional information about sources of error (such as clock drift, ephemeris, or ionospheric delay), others provide direct measurements of how much the signal was off in the past, while a third group provides additional vehicle information to be integrated in the calculation process. Satellite-based augmentation system Satellite-based augmentation systems (SBAS) support wide-area or regional augmentation through the use of additional satellite-broadcast messages. Using measurements from the ground stations, correction messages are created and sent to one or more

Doppler-based positioning using LEO augmented satellite constellation - Simulations of perspectives

Alice Andreetti

The Global Navigation Satellite System (GNSS) refers to a constellation of satellites emitting signals from space, used to provide Position, Navigation and Timing (PNT) services to the receivers on Earth. Nowadays, the GNSS is exploited in a wide range of applications among which ground mapping, transportation, machine control, timing, surveying, defense, or aerial photogrammetry [1]. However, as we become more dependent on GNSS technology, we also become more vulnerable to its limitations [2]. The GNSS operates with satellites orbiting in Medium Earth Orbits (MEO, approximately 20200 [km] in altitude). On one hand, this great distance allows to have a large footprint of the satellite signal on Earth, but on the other hand, it requires the signal to cross a wide path in the atmosphere before reaching the receiver. This results in a decrease of signal strength, which is not an issue in open-sky condition, but becomes a limitation in deep attenuation environments, with little or no service in urban canyon, in dense cities or indoors [3]. In this contribution, a possible strategy to cope with this issue is proposed and evaluated through a simulation process. It implies the use of Low Earth Orbits (LEO) satellites as a support for the GNSS PNT service. Since nowadays no broadband big LEO constellation broadcasting navigation messages exist, in this project various LEO constellation setups have been simulated and tested. Because LEOs are much closer to Earth (200 to 1500 [km]), they move faster in the sky, passing overhead in minutes instead of hours like MEOs. This gives rise to the possibility to exploit the Doppler effect to accurately locate the user. Therefore, three different PNT algorithms, employing the Kalman filter, are implemented and the evaluation of the localization quality is made at four distinct locations on the globe. The results show that, for most of the cases, compared to the standard GPS pseudorange only PNT, the addition of LEO pseudoranges already improve the localization quality. The performance of the PNT algorithm increases even more with the exploitation of both pseudoranges and pseudorangerates (Doppler) measurements. Nevertheless, the choice of constellation parameters such as satellites altitude, total number of satellites, orbit inclination or the frequency of the emitted signal, has a great impact on the magnitude of the improvement in the localization quality. The factor that has the most significant influence seems to be the signal frequency and for that reason it must be carefully chosen: the higher the better. Moreover, it has been demonstrated that at high elevation cut-off angles (denied environments), the addition of LEO constellation is a valid option and allows us to obtain an accurate position even when the GNSS only can not provide a solution. Finally, the LEO only system seems to be a promising alternative to cope with GNSS jamming or spoofing. However, the optimal LEO parameters providing an accurate solution for all the location on the globe has not yet been identified. In conclusion, the result of this effort is the awareness that, once the optimal parameters for the LEO system have been found, it is a valid option to augment the GNSS, or even as a standalone backup, especially when the Doppler-based positioning is applied. Nevertheless, we are still far from that end and much more research needs to be done.

2020

Lidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks

Aurélien Arnaud Brun, Davide Antonio Cucci, Jan Skaloud

With the objective of improving the registration of lidar point clouds produced by kinematic scanning systems, we propose a novel trajectory adjustment procedure that leverages on the automated extraction of selected reliable 3D point–to–point correspondences between overlapping point clouds and their joint integration (adjustment) together with raw inertial and GNSS observations. This is performed in a tightly coupled fashion using a dynamic network approach that results in an optimally compensated trajectory through modeling of errors at the sensor, rather than the trajectory, level. The 3D correspondences are formulated as static conditions within the dynamic network and the registered point cloud is generated with significantly higher accuracy based on the corrected trajectory and possibly other parameters determined within the adjustment. We first describe the method for selecting correspondences and how they are inserted into the dynamic network via new observation model while providing an open-source implementation of the solver employed in this work. We then describe the experiments conducted to evaluate the performance of the proposed framework in practical airborne laser scanning scenarios with low-cost MEMS inertial sensors. In the conducted experiments, the method proposed to establish 3D correspondences is effective in determining point–to–point matches across a wide range of geometries such as trees, buildings and cars. Our results demonstrate that the method improves the point cloud registration accuracy (~5x in nominal and ~10x in emulated GNSS outage conditions within the studied cases), which is otherwise strongly affected by errors in the determined platform attitude or position, and possibly determine unknown boresight angles. The proposed methods remain effective even if only a fraction (~0.1%) of the total number of established 3D correspondences are considered in the adjustment.

2022

On the benefit of concurrent adjustment of active and passive optical sensors with GNSS & raw inertial data

Davide Antonio Cucci, Kyriaki Mouzakidou, Jan Skaloud

In airborne laser scanning a high-frequency trajectory solution is typically determined from inertial sensors and employed to directly geo-reference the acquired laser points. When low-cost MEMS inertial sensors are used, such as in lightweight unmanned aerial vehicles, non-negligible errors in the estimated trajectory project to the final point-cloud, resulting in unsatisfactory accuracy on the ground. There are different multi-sensor fusion approaches to correct the point-cloud errors caused by an imperfect trajectory determination. Mismatches between different optical observations and/or in the overlapping regions of the point-cloud can allow the correction of the final point-cloud, either directly, by means of rigid transformations, or indirectly, via improving the scanner trajectory estimation. In this work we propose to fuse lidar and cameras in a single adjustment based on dynamic networks, considering 2D tie-points from the imagery and 3D tie-points from overlapping point-cloud sections. On a challenging corridor mapping scenario, we show that considering either 2D or 3D tie-points, along with inertial and GNSS observations, results in a remarkably accurate point-cloud, even when low-cost inertial sensors are employed and in presence of challenging surface textures, such as high vegetation. Furthermore, since the distribution of the 2D and 3D tie-points is complementary, considering them together further increases the robustness of the adjustment due to higher redundancy. By employing the proposed approach within this controlled example, we were able to improve the final point-cloud accuracy by more than three times with respect to conventional geo-referencing methodology and to reduce the magnitude of the errors.

2022

Doppler-based positioning using LEO augmented satellite constellation - Simulations of perspectives

Alice Andreetti

2020

Lidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks

Aurélien Arnaud Brun, Davide Antonio Cucci, Jan Skaloud

2022