On Fault Detection and Exclusion in Snapshot and Recursive Positioning Algorithms for Maritime Applications

Resilient provision of Position, Navigation and Timing (PNT) data can be considered as a key element of the e-Navigation strategy developed by the International Maritime Organization (IMO). An indication of reliability has been identified as a high level user need with respect to PNT data to be supplied by electronic navigation means. The paper concentrates on the Fault Detection and Exclusion (FDE) component of the Integrity Monitoring (IM) for navigation systems based both on pure GNSS (Global Navigation Satellite Systems) as well as on hybrid GNSS/inertial measurements. Here a PNT-data processing Unit will be responsible for both the integration of data provided by all available on-board sensors as well as for the IM functionality. The IM mechanism can be seen as an instantaneous decision criterion for using or not using the system and, therefore, constitutes a key component within a process of provision of reliable navigational data in future navigation systems. The performance of the FDE functionality is demonstrated for a pure GNSS-based snapshot weighted iterative least-square (WLS) solution, a GNSS-based Extended Kalman Filter (EKF) as well as for a classical error-state tightly-coupled EKF for the hybrid GNSS/inertial system. Pure GNSS approaches are evaluated by combining true measurement data collected in port operation scenario with artificially induced measurement faults, while for the hybrid navigation system the measurement data in an open sea scenario with native GNSS measurement faults have been employed. The work confirms the general superiority of the recursive Bayesian scheme with FDE over the snapshot algorithms in terms of fault detection performance even for the case of GNSS-only navigation. Finally, the work demonstrates a clear improvement of the FDE schemes over non-FDE approaches when the FDE functionality is implemented within a hybrid integrated navigation system

Safe navigation for vehicles

La navigation par satellite prend un virage très important ces dernières années, d'une part par l'arrivée imminente du système Européen GALILEO qui viendra compléter le GPS Américain, mais aussi et surtout par le succès grand public qu'il connaît aujourd'hui. Ce succès est dû en partie aux avancées technologiques au niveau récepteur, qui, tout en autorisant une miniaturisation de plus en plus avancée, en permettent une utilisation dans des environnements de plus en plus difficiles. L'objectif aujourd'hui est de préparer l'utilisation de ce genre de signal dans une optique bas coût dans un milieu urbain automobile pour des applications critiques d'un point de vue sécurité (ce que ne permet pas les techniques d'hybridation classiques). L'amélioration des technologies (réduction de taille des capteurs type MEMS ou Gyroscope) ne peut, à elle seule, atteindre l'objectif d'obtenir une position dont nous pouvons être sûrs si nous utilisons les algorithmes classiques de localisation et d'hybridation. En effet ces techniques permettent d'avoir une position sans cependant permettre d'en quantifier le niveau de confiance. La faisabilité de ces applications repose d'une part sur une recherche approfondie d'axes d'amélioration des algorithmes de localisation, mais aussi et conjointement, sur la possibilité, via les capteurs externes de maintenir un niveau de confiance élevé et quantifié dans la position même en absence de signal satellitaire. ABSTRACT : Satellite navigation has acquired an increased importance during these last years, on the one hand due to the imminent appearance of the European GALILEO system that will complement the American GPS, and on the other hand due to the great success it has encountered in the commercial civil market. An important part of this success is based on the technological development at the receiver level that has rendered satellite navigation possible even in difficult environments. Today's objective is to prepare the utilisation of this kind of signals for land vehicle applications demanding high precision positioning. One of the main challenges within this research domain, which cannot be addressed by classical coupling techniques, is related to the system capability to provide reliable position estimations. The enhancement in dead-reckoning technologies (i.e. size reduction of MEMS-based sensors or gyroscopes) cannot all by itself reach the necessary confidence levels if exploited with classical localization and integration algorithms. Indeed, these techniques provide a position estimation whose reliability or confidence level it is very difficult to quantify. The feasibility of these applications relies not only on an extensive research to enhance the navigation algorithm performances in harsh scenarios, but also and in parallel, on the possibility to maintain, thanks to the presence of additional sensors, a high confidence level on the position estimation even in the absence of satellite navigation signals

RNN-Based GNSS Positioning using Satellite Measurement Features and Pseudorange Residuals

In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has lead to many challenges when it comes to choosing the most accurate pseudorange contributions, given the strong impact of biased measurements on positioning accuracy, particularly in single-epoch scenarios. This work leverages the potential of machine learning in predicting link-wise measurement quality factors and, hence, optimize measurement weighting. For this purpose, we use a customized matrix composed of heterogeneous features such as conditional pseudorange residuals and per-link satellite metrics (e.g., carrier-to-noise power density ratio and its empirical statistics, satellite elevation, carrier phase lock time). This matrix is then fed as an input to a recurrent neural network (RNN) (i.e., a long-short term memory (LSTM) network). Our experimental results on real data, obtained from extensive field measurements, demonstrate the high potential of our proposed solution being able to outperform traditional measurements weighting and selection strategies from state-of-the-art

Robust Positioning in the Presence of Multipath and NLOS GNSS Signals

GNSS signals can be blocked and reflected by nearby objects, such as buildings, walls, and vehicles. They can also be reflected by the ground and by water. These effects are the dominant source of GNSS positioning errors in dense urban environments, though they can have an impact almost anywhere. Non- line-of-sight (NLOS) reception occurs when the direct path from the transmitter to the receiver is blocked and signals are received only via a reflected path. Multipath interference occurs, as the name suggests, when a signal is received via multiple paths. This can be via the direct path and one or more reflected paths, or it can be via multiple reflected paths. As their error characteristics are different, NLOS and multipath interference typically require different mitigation techniques, though some techniques are applicable to both. Antenna design and advanced receiver signal processing techniques can substantially reduce multipath errors. Unless an antenna array is used, NLOS reception has to be detected using the receiver's ranging and carrier-power-to-noise-density ratio (C/N0) measurements and mitigated within the positioning algorithm. Some NLOS mitigation techniques can also be used to combat severe multipath interference. Multipath interference, but not NLOS reception, can also be mitigated by comparing or combining code and carrier measurements, comparing ranging and C/N0 measurements from signals on different frequencies, and analyzing the time evolution of the ranging and C/N0 measurements

Safe navigation for vehicles

Satellite navigation has acquired an increased importance during these last years, on the one hand due to the imminent appearance of the European GALILEO system that will complement the American GPS, and on the other hand due to the great success it has encountered in the commercial civil market. An important part of this success is based on the technological development at the receiver level that has rendered satellite navigation possible even in difficult environments. Today's objective is to prepare the utilisation of this kind of signals for land vehicle applications demanding high precision positioning. One of the main challenges within this research domain, which cannot be addressed by classical coupling techniques, is related to the system capability to provide reliable position estimations. The enhancement in dead-reckoning technologies (i.e. size reduction of MEMS-based sensors or gyroscopes) cannot all by itself reach the necessary confidence levels if exploited with classical localization and integration algorithms. Indeed, these techniques provide a position estimation whose reliability or confidence level it is very difficult to quantify. The feasibility of these applications relies not only on an extensive research to enhance the navigation algorithm performances in harsh scenarios, but also and in parallel, on the possibility to maintain, thanks to the presence of additional sensors, a high confidence level on the position estimation even in the absence of satellite navigation signals

Benefits from a multi-receiver architecture for GNSS precise positioning

Precise positioning with a stand-alone GPS receiver or using differential corrections is known to be strongly degraded in an urban or sub-urban environment due to frequent signal masking, strong multipath effect, frequent cycle slips on carrier phase, etc. The objective of this Ph.D. thesis is to explore the possibility of achieving precise positioning with a low-cost architecture using multiple installed low-cost single-frequency receivers with known geometry whose one of them is RTK positioned w.r.t an external reference receiver. This setup is thought to enable vehicle attitude determination and RTK performance amelioration. In this thesis, we firstly proposed a method that includes an array of receivers with known geometry to enhance the performance of the RTK in different environments. Taking advantage of the attitude information and the known geometry of the installed array of receivers, the improvement of some internal steps of RTK w.r.t an external reference receiver can be achieved. The navigation module to be implemented in this work is an Extended Kalman Filter (EKF). The performance of a proposed two-receiver navigation architecture is then studied to quantify the improvements brought by the measurement redundancy. This concept is firstly tested on a simulator in order to validate the proposed algorithm and to give a reference result of our multi-receiver system’s performance. The pseudorange measurements and carrier phase measurements mathematical models are implemented in a realistic simulator. Different scenarios are conducted, including varying the distance between the 2 antennas of the receiver array, the satellite constellation geometry, and the amplitude of the noise measurement, in order to determine the influence of the use of an array of receivers. The simulation results show that our multi-receiver RTK system w.r.t an external reference receiver is more robust to noise and degraded satellite geometry, in terms of ambiguity fixing rate, and gets a better position accuracy under the same conditions when compared with the single receiver system. Additionally, our method achieves a relatively accurate estimation of the attitude of the vehicle which provides additional information beyond the positioning. In order to optimize our processing, the correlation of the measurement errors affecting observations taken by our array of receivers has been determined. Then, the performance of our real-time single frequency cycle-slip detection and repair algorithm has been assessed. These two investigations yielded important information so as to tune our Kalman Filter. The results obtained from the simulation made us eager to use actual data to verify and improve our multi-receiver RTK and attitude system. Tests based on real data collected around Toulouse, France, are used to test the performance of the whole methodology, where different scenarios are conducted, including varying the distance between the 2 antennas of the receiver array as well as the environmental conditions (open sky, suburban, and constrained urban environments). The thesis also tried to take advantage of a dual GNSS constellation, GPS and Galileo, to further strengthen the position solution and the reliable use of carrier phase measurements. The results show that our multi-receiver RTK system is more robust to degraded GNSS environments. Our experiments correlate favorably with our previous simulation results and further support the idea of using an array of receivers with known geometry to improve the RTK performance

A Portfolio Approach to NLOS and Multipath Mitigation in Dense Urban Areas

Non-line-of-sight (NLOS) reception and multipath interference are major causes of poor GNSS positioning accuracy in dense urban environments. They are commonly grouped together. However, both the mechanisms by which they cause position errors and many of the techniques for mitigating those errors are quite different [1]. For example, correlation-based multipath mitigation has no effect on the errors caused by NLOS reception. University College London (UCL) has investigated the performance of a number of multipath and/or NLOS mitigation techniques in dense urban areas, including C/N0-based solution weighting [2], advanced consistency checking [3], dual-polarization NLOS detection [4] and vector tracking [5]. In this paper, we present a new multipath detection technique based on comparing the measured C/N0 on multiple frequencies and also new dual-polarization results. Meanwhile, other researchers have demonstrated NLOS detection using a panoramic camera [6, 7] or 3D city model [8, 9] and detection of NLOS and multipath using an antenna array [10]. All of these techniques bring some improvement in positioning performance in urban environments, but none of them eliminate the effects of both NLOS reception and multipath interference completely. As the different techniques are largely complementary, best performance is obtained by using several of them in combination, a portfolio approach. This paper comprises three parts. The first presents a feasibility study on a new multipath detection technique using multi-frequency C/N0 measurements. Constructive multipath interference results in an increase in the measured C/N0, whereas destructive multipath interference results in a decrease. As the phase of a reflected signal with respect to its directly received counterpart depends on the wavelength, the multipath interference may be constructive on one frequency and destructive on another. Thus, by comparing the difference in measured C/N0 between two frequencies with what would normally be expected for that signal at that elevation angle, strong multipath interference may be detected. However, the converse is not true because, depending on the path delay, the phase of the multipath interference may also be consistent across the two frequencies. Consistency across three frequencies in the presence of multipath interference is much less likely than consistency across two. Therefore, by comparing C/N0 measured across three (or more) frequencies, the chance of detection is improved substantially, noting that reliability is less critical as part of a portfolio approach to multipath detection than for a stand-alone technique. Experimental results are presented demonstrating the potential of this approach using GPS and GLONASS data collected in Central London. The second part of the paper presents the results of the first multi-constellation test of the dual-polarization NLOS detection technique pioneered at UCL [4]. This separately correlates the right hand circularly polarized (RHCP) and left hand circularly polarized (LHCP) outputs of a dual-polarization antenna and differences the resulting C/N0 measurements, producing a result that is positive for directly received signals and negative for most NLOS signals. Data was collected at six different sites in Central London and NLOS reception of both GPS and GLONASS signals was detected. Position solutions with the NLOS signals removed are compared with the corresponding all-satellite solutions. The final part of the paper addresses the portfolio approach to NLOS and multipath mitigation. Each technique is assessed qualitatively for its ease of implementation and its efficiency at detecting or directly mitigating both NLOS reception and multipath mitigation. A compatibility matrix is then presented showing which techniques may be combined without conflict. Suitable portfolios are then proposed both for professional-grade and for consumer-grade user equipment. References [1] Groves, P. D., Principles of GNSS, inertial, and multi-sensor integrated navigation systems, Second Edition, Artech House, 2013. [2] Jiang, Z., P. Groves, W. Y. Ochieng, S. Feng, C. D. Milner, and P. G. Mattos, “Multi-Constellation GNSS Multipath Mitigation Using Consistency Checking,” Proc. ION GNSS 2011. [3] Jiang, Z., and P. Groves, “GNSS NLOS and Multipath Error Mitigation using Advanced Multi-Constellation Consistency Checking with Height Aiding,” Proc. ION GNSS 2012. [4] Jiang, Z., and P. D. Groves, “NLOS GPS Signal Detection Using A Dual-Polarisation Antenna,” GPS Solutions, 2012, DOI: 10.1007/s10291-012-0305-5. [5] Hsu, L.-T., P. D. Groves, and S.-S. Jan, “Assessment of the Multipath Mitigation Effect of Vector Tracking in an Urban Environment,” Proc ION Pacific PNT, 2013. [6] Marais, J., M. Berbineau, and M. Heddebaut, “Land Mobile GNSS Availability and Multipath Evaluation Tool,” IEEE Transactions on Vehicular Technology, Vol. 54, No. 5, 2005, pp. 1697-1704. [7] Meguro, J., et al., “GPS Multipath Mitigation for Urban Area Using Omnidirectional Infrared Camera,” IEEE Transactions on Intelligent Transportation Systems, Vol. 10, No. 1, 2009, pp. 22-30. [8] Obst, M., S. Bauer, and G. Wanielik, “Urban Multipath Detection and mitigation with Dynamic 3D Maps for Reliable Land Vehicle Localization,” Proc. IEEE/ION PLANS 2012. [9] Peyraud, S., et al., “About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm,” Sensors, Vol. 13, 2013, pp. 829-847. [10] Keshvadi, M. H., A. Broumandan, and G. Lachapelle, “Analysis of GNSS Beamforming and Angle of Arrival Estimation in Multipath Environments," Proc ION ITM, San Diego, CA, January 2011, pp. 427-435

Advanced Integration of GNSS and External Sensors for Autonomous Mobility Applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

New on-board multipurpose architecture integrating modern estimation techniques for generalized GNSS based autonomous orbit navigation

This dissertation investigates a novel Multipurpose Earth Orbit Navigation System (MEONS) architecture aiming at providing a generalized GNSS based spacecraft orbit estimation kernel matching the modern navigation instance of enhanced flexibility with respect to multiple Space Service Volume (SSV) applications (Precise Orbit Determination for Earth Observation satellite, Low Thrust Low to High Autonomous Orbit Rising, formation flying relative navigation, Small Satellite Autonomous Orbit Acquisition). The possibility to address theoretical and operational solutions within a unified framework is a foundamental step for the implementation of a reusable and configurable high performance navigation capability on next generation platforms

GNSS Shadow Matching: The Challenges Ahead

GNSS shadow matching is a new technique that uses 3D mapping to improve positioning accuracy in dense urban areas from tens of meters to within five meters, potentially less. This paper presents the first comprehensive review of shadow matching’s error sources and proposes a program of research and development to take the technology from proof of concept to a robust, reliable and accurate urban positioning product. A summary of the state of the art is also included. Error sources in shadow matching may be divided into six categories: initialization, modelling, propagation, environmental complexity, observation, and algorithm approximations. Performance is also affected by the environmental geometry and it is sometimes necessary to handle solution ambiguity. For each error source, the cause and how it impacts the position solution is explained. Examples are presented, where available, and improvements to the shadow-matching algorithms to mitigate each error are proposed. Methods of accommodating quality control within shadow matching are then proposed, including uncertainty determination, ambiguity detection, and outlier detection. This is followed by a discussion of how shadow matching could be integrated with conventional ranging-based GNSS and other navigation and positioning technologies. This includes a brief review of methods to enhance ranging-based GNSS using 3D mapping. Finally, the practical engineering challenges of shadow matching are assessed, including the system architecture, efficient GNSS signal prediction and the acquisition of 3D mapping data