GNSS/IMU Tightly Coupled Scheme with Weighting and FDE for Rail Applications

Abstract

Her research focuses on performance evaluation of integrated navigation system. She worked within Ifsttar for an internship in the summer 2019.Dr. Juliette Marais received the engineering degree from Institut Supérieur de l'Electronique et du Numérique. She received the Ph.D. degree in electronics and the "Habilitation à diriger des recherches" from the University of Lille, France, in 2002 and 2017 respectively. Since 2002, she has been a research fellow with IFSTTAR, the French Institute of science and technology for transport, development, and networks. She is involved on two main research projects: integrity monitoring for land transport applications and GNSS propagation characterization in railway environments, with some contributions in EU or national projects. Her research interests principally include propagation phenomena, positioning and pseudorange error modeling, filtering technics, and simulation. Syed Ali Kazim works as a research engineer at IFSTTAR, the French Institute of science and technology for transport, development, and networks since 2018. His current research interests focus on multipath detection, modelling and mitigation. He is involved in European projects such as ERSAT GGC and Gate4Rail.Nourdine Aït Tmazirte works at French Institute of Technology Railenium since 2018. He got his engineering and M.Sc. degree in automation engineering from Ecole Centrale de Lille, France, both in 2010. His research interests include multi-sensor fault tolerant fusion for localization and integrity assessment. Dr.-Ing. Debiao Lu works at faculty of Electronic and Information Engineering at Beijing Jiaotong University in China since 2015. He got his doctor title at faculty of Mechanical Engineering at Technische Universität Braunschweig, Germany in 2014. He received the B.Sc. degree in telecommunication engineering and M.Sc. degree in traffic information engineering and control, both at Beijing Jiaotong University in China. His research interests include GNSS safe localization, GNSS propagation simulation and performance assessment.ABSTRACT GNSS used as a standalone positioning system fulfils most of the requirements for many applications since decades. However, the need of high available, accurate and fail-safe positioning systems for new applications such as rail autonomous vehicles for train signaling applications motivates the community to explore novel solutions. In this context, multi-constellation multi-frequency GNSS receivers have the potential to enhance the positioning solutions. However, when applied to safety-critical land transportation system, the localization function not only needs to meet accuracy requirements, but more importantly, it also needs to bound the positioning errors in order to reduce the risk of unexpected and undetected faults. Thus, in order to reach continuous and fail-safe positioning solutions, the use of complementary heterogeneous sensors with a smart hybridization becomes essential. For safety-related and regulated applications as in railways, one will also need, as ...

Case study of Bayesian RAIM algorithm integrated with Spatial Feature Constraint and Fault Detection and Exclusion algorithms for multi‐sensor positioning

“…For example, Pervan (1996) and Enge (1999) demonstrate navigation integrity method for aircraft precision landing using GNSS and ground‐based pseudolites, which ensure sufficient measurement redundancy. To the authors' best knowledge, the most common multi‐sensor integrity solutions for land vehicles are based on the integration of GNSS, Inertial Measurement Units (IMU), and odometer or speedometer (Han et al., 2020; W. Liu et al., 2020; El‐Mowafy & Kubo, 2017; Toledo‐Moreo et al., 2010). Maaref et al.…”

“…(2019); Han et al. (2020); Maaref et al. (2018); El‐Mowafy et al.…”

“…(2020) propose and implement different FDE methods for the purpose of integrity monitoring. However, a lot of available literature requires measurement redundancy of at least six measurements to remove one fault (Han et al., 2020; El‐Mowafy et al., 2020) or is only able to consider one fault at each time‐stamp (J. Liu et al., 2020; Maaref et al., 2018). An FDE method capable of excluding a single fault even if classic RAIM is not possible is proposed by J. Liu et al.…”

Navigation Context Adaptive Fault Detection and Exclusion Strategy based On Deep Learning & Information Theory: Application to a GNSS/IMU Integration

“…To overcome this problem, mitigation techniques also known as fault management or fault tolerance make it possible to reduce unavailability by isolating the suspicious measurement(s). But it is essential to prove that the taken measure(s), for instance a measurement exclusion, or a reweighting procedure, is(are) the right one(s) [6]. To cite an example, it is necessary to prove that an excluded measure should indeed be excluded and that it is the only one that should be excluded.…”