Our NEWS
2026/01/02
🎉 Abbia Celebrates 20 Years of Innovation and Partnership! 🎉
We are thrilled to announce that Abbia is celebrating its 20th anniversary!
Since our founding in 2006 in Toulouse, France, ABBIA has been driven by a passion for excellence in engineering, research, and innovation, especially in GNSS technologies, data science, and biomedical engineering.
This milestone is a tribute to the dedication of our talented team, the trust of our clients and partners, and our shared commitment to delivering innovative cutting-edge solutions. After years of pushing boundaries and embracing new challenges, we will strive to evolve while staying true to our core values of quality and collaboration.
Thank you to everyone who has been part of the Abbia journey. Your support inspires us to reach even greater heights.
The Abbia team.
2025/09/02
The European Space Agency (ESA) has acknowledged the work of ABBIA GNSS Technologies with an award presented during the commemorative event “30 Years of European Satellite Navigation”, held at the European Space Research and Technology Centre (ESTEC) in Noordwijk, the Netherlands, on 2 September. The award highlights ABBIA’s in recognition of its Excellence in GNSS Engineering, Commitment and long-standing Partnership leading to the success of European Satellite Navigation programmes.
The event, marking three decades since the launch of Europe’s satellite navigation initiative, brought together over a hundred representatives from institutions, member states, and companies, and featured the participation of ESA Director General Josef Aschbacher and ESA Director of Navigation Javier Benedicto.
Representing ABBIA GNSS Technologies, Bertrand Ekambi, its Founder-Manager, accepted the award during the ceremony. The company has expressed its gratitude for the recognition, which reflects its commitment to scientific excellence and collaboration in European space programmes.
2025/05/21-23
ABBIA DATA SCIENCE participated to ENC 2025 in Wroclaw, Poland, in May.
We presented an R&D paper entitled « Toward an Interpretable Multipath Error Model from GNSS Observables through the Application of Deep Learning ».
Multipath degradation of GNSS measurements is the main source of error in urban areas. Robust mitigation of this error source is still a challenge for standalone low-cost GNSS receivers. The complexity associated with the development of Multipath degradation models requires the use of advanced methods such as Deep Learning.
However, Deep Learning based mitigation methods tend to be hard to deploy due to a general lack of trust in their prediction due to their “black-box” behavior. This work tackles the notion of interpretability and generalization of Multipath degradation models obtained using Auto-Encoders.
We demonstrate the ability of Auto-Encoders to generate interpretable representations and to generalize to unseen situations.
Keywords: Data Science, GNSS, Deep Learning, Multipath, Self-Supervised Learning, Auto-Encoder, Interpretability