PhD Student Toulouse / Barcelona in GNSS / Factor Graph Optimization (FGO)

This position has been filled. Thanks for you interest.

Title: Towards Centimeter-Level Kinematic Positioning with GNSS Receivers using Factor Graph Optimization
Contract type: Contrat à Durée Déterminée de 3 ans
Start date: 01-Oct-2022
Workplace: ENAC Toulouse, with possibility of stay at IRI-CSIC Barcelona
Salary: 2150€ (gross)

Application deadline: 24-Jul-2022
Required diploma: Master degree in electrical engineering
Required skills: Experience with GNSS or SLAM technique is a plus.

Send application to thevenon(at), jsola(at), julien.lesouple(at)

Organisation of the PhD study

The PhD candidate will be employed by ENAC in Toulouse, with possibility to organize short or long stays (up to 1 year) at IRI in Barcelona, at the convenience of the candidate. The gross salary is expected to be 2150 € per month, with possibility to perform a few additional paid teaching activities.

The PhD study is co-supervised by 2 institutions: ENAC and IRI-CSIC.

ENAC (Ecole Nationale de l’Aviation Civile) is the French Civil Aviation School, based in Toulouse. It provides numerous higher education programs ranging from Bachelor to Master of Science, Aviation Advanced Master, Master of Business and Administration as well as Ph.D.s in the domains of aeronautics and aviation. The SIGNAV (Signal Processing for Navigation) research group of ENAC has a worldwide recognized technical and operational expertise in all fields and systems (current and under development) related to the use of GNSS by civil aviation: SBAS, GBAS, ABAS (RAIM, AAIM, ARAIM). The SIGNAV research group has developed a strong expertise regarding land applications requiring a navigation platform with a high quality of service for safety, liability or financial reasons. The SIGNAV research group is also strongly involved in the development of low-cost precise positioning platforms for urban environments. The SIGNAV research group has published over 150 papers, supervised over 27 PhD students and cooperated in more than 70 expertise contracts since its creation in 1993.

IRI (Institut de Robòtica i Informàtica Industrial) is a Joint Research Center of the Spanish Council for Scientific Research (CSIC) and the Technical University of Catalonia (UPC). The Institute has three main objectives: to promote fundamental research in Robotics and Applied Informatics, to cooperate with the community in industrial technological projects, and to offer scientific education through graduate courses.

Topic Overview

The introduction of low-cost, multi-constellation, multi-frequency GNSS chipsets, such as those available in the latest smartphones, has brought us closer to global low-cost decimeter-level positioning, so it is time to establish a more ambitious target. One heuristic to do so is to boost accuracy requirements by an order of magnitude. This document provides a big-picture view of positioning accuracy achievable today with low-cost hardware and outlines one of the research perspectives that have the potential to bring us to the centimeter level.

Up to now, most GNSS-based solutions are based on estimation techniques derived from Kalman Filtering. However, recent works on optimization-based techniques have received publicity, thanks to their superior performances in harsh GNSS environment such as urban centers, where GNSS observations are affected by multipath.

Contrary to filtering techniques, optimization-based techniques can apply the estimation process over a wider range of epochs, from the start of the receiver up to the latest available observations. By performing an optimization process over all the available observations at every epoch, the overall accuracy is improved. Factor Graph Optimization (FGO) seems to be a promising framework for such optimization. Two particularities have brought major improvements to such technique:
1. the use of Switchable Constraints, which allows to weight each GNSS observation at every epoch, so as to exclude those affected by large multipath errors,
2. the use of Time-Relative RTK solutions, which consists of a decimeter- or centimeter-level relative position constraint between two epochs of the trajectory, provided by using a differential GNSS solution from the same receiver between two epochs of the trajectory, where the GNSS carrier ambiguities can be successfully fixed. This constraint can be seen as similar to a loop closure constraint in visual SLAM techniques.

The latest results using those two features using only GNSS observations have shown to provide better accuracy than a hybridization between GNSS and low-cost IMU observations, during the 2021 Google Smartphone Decimeter Challenge [Suzuki 2021].

Optimization techniques for GNSS position, velocity and timing is therefore a currently hot topic, where many things have still to be validated. What kind of GNSS observations and which GNSS models are the best suited for this framework, notably between a differential solution (RTK), or a standalone one (PPP)? Can some epochs be considered as anchors for computing successful TR-RTK constraints? Do some simplifications need to be done in order to reduce the required processing power? How to ensure a good quality Time-Relative RTK solution within a trajectory? Can this technique be applied in real-time? Can position integrity be ensured with this framework?

This technique will be first investigated offline on large GNSS datasets, such as SmartLoc [Reisdorf 2016], Google Smartphone Decimeter Challenge [Fu 2020], UrbanNav [Hsu 2021]. Depending on the results, the study could also incorporate hybridization with IMU sensors, as FGO has been widely used for sensor fusion and in particular for GNSS and IMU [Wen 2021]

This PhD will benefit from the supervision by two laboratories: ENAC/TELECOM/SIGNAV team which specializes in the processing of GNSS observations, and IRI-CSIC team which specializes in visual SLAM techniques, where the optimization framework has largely been used.


[Fu 2020]

Fu, Guoyu (Michael), Khider, Mohammed, van Diggelen, Frank, “Android Raw GNSS Measurement Datasets for Precise Positioning,” Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020), September 2020, pp. 1925-1937.

[Hsu 2021]

Hsu, Li-Ta, Kubo, Nobuaki, Wen, Weisong, Chen, Wu, Liu, Zhizhao, Suzuki, Taro, Meguro, Junichi, “UrbanNav:An Open-Sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas,” Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 226-256.

[Liu 2020]

Liu, Xiao, Ribot, Miguel Ángel, Gusi-Amigó, Adrià, Closas, Pau, Garcia, Adrià Rovira, Subirana, Jaume Sanz, “RTK Feasibility Analysis for GNSS Snapshot Positioning,” Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020), September 2020, pp. 2911-2921.

[Reisdorf 2016]

Reisdorf, P., Pfeifer, T., Breßler, J., Bauer, S., Weissig, P., Lange, S., Wanielik, G., Protzel, P. (2016). The Problem of Comparable GNSS Results – An Approach for a Uniform Dataset with Low-Cost and Reference Data. Proceedings of International Conference on Advances in Vehicular Systems, Technologies and Applications, 5:8, ISSN: 2327-2058.

[Sünderhauf 2012a]

Sünderhauf, N., Protzel, P. “Switchable constraints for robust pose graph SLAM,” 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012, pp. 1879-1884,

[Sünderhauf 2012b]

Sünderhauf, N., Obst, M., Wanielik, G. & Protzel, P. (2012) Multipath Mitigation in GNSS-Based Localization using Robust Optimization. In Proc. of IEEE Intelligent Vehicles Symposium (IV).

[Suzuki 2020]

Suzuki, T. “Time-Relative RTK-GNSS: GNSS Loop Closure in Pose Graph Optimization,” in IEEE Robotics and Automation Letters, vol. 5, no. 3, pp. 4735-4742, July 2020,

[Suzuki 2021]

Suzuki, Taro, “First Place Award Winner of the Smartphone Decimeter Challenge: Global Optimization of Position and Velocity by Factor Graph Optimization,” Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 2974-2985.

[Teunissen 2017]

Teunissen, P. J. G., & Montenbruck, O. (Eds.). (2017). “Springer Handbook of Global Navigation Satellite Systems.”

[Wen 2021]

Wen, W., Pfeifer, T., Bai, X., & Hsu, L. T. (2021). Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter. NAVIGATION, Journal of the Institute of Navigation, 68(2), 315-331.