Thales Alenia Space

Acronym: 
TAS FR & IT
Country: 
France

Thales Alenia Space (TAS), a joint venture between Thales (67%) and Leonardo (33%), is a key European player in space telecommunications, navigation, Earth observation, exploration and orbital infrastructures. TAS also teams up with Telespazio to form the parent companies’ “Space Alliance”, which offer a complete range of services and solutions. TAS posted consolated revenues of about 2.4 billion in 2016 and has 7,980 employees in nine countries. The company is deeply involved in:

  • Environmental projects based on Earth Observation such as the Copernicus program, Meteosat third generation and the PUMA program, providing meterological stations in 46 African countries.
  • Altimetry instrument for ocean and inland water bodies level measurement (TAS is number one worldwide)
  • Defence with major programs such as the French Syracuse (I, II and III) and the Italian (Sicral) telecommunication satellites; and in very-high-resolution instruments on French intelligence satellites (Helios, Pleiades, CSO families) , COSMO-SkyMed (Italy) and SAR-Lupe (Germany).

Key personnel 

Romain Hugues: Remote Sensing, EO Big Data Analytics and Imaging Chain engineer. He holds a Master Degree in Signal and Automatics for Embedded Systems from the ENSTA-Bretagne, France since 2007. After a three years’ experience developing automatic navigation, cartography and metrology systems based on video image processing at Fugro Intersite B.V. in the Netherlands, he joined Thales Alenia Space in 2010. Since then, he has been involved in the design and validation of image processing algorithms in the extent of the imaging chain:

  • Imaging Chain Simulation: Image Quality, Performance assessment and sizing of a Geostationary satellite observing in the infrared
  • Space-born Imaging Chain: Image compression, Active Optics
  • Upstream Ground Segment: Design, and validation of High Resolution Optical Data Production algorithms, Responsible for Internal studies in Big Data EO analytics & Deep Learning
  • Downstream and application: Design Authority for Radar and Optical Remote Sensing System

Marc Spigai: Image Processing and machine learning Expert. He holds a Master Degree in signal and image processing from the ENST-Bretagne, France in 1989. After an eight-year’ experience developing data science on estimation, filtering, tracking at Thales Airborne System in France, he joined Renault in France from 1998 to 2000 where he was the head of a research team (10 persons) on image, radar and GPS fusion for driver assistance. He joined in 2000 Thales Alenia Space (TAS) at Toulouse in France. Since then, he has been involved in image processing for remote sensing applications. In particular from 2014 to 2016 he worked for TAS at the research institute IRT Saint-Exupery in the field of machine and deep learning for remote sensing imagery applications. In 2017 he comes back at TAS as expert in Deep Learning and Artificial Intelligence.

Michelle Aubrun: Remote Sensing engineer. She holds two Master Degrees in surveying from ESTP and in geomatics from ENSG, France in 2013. After a Ph.D. at University of Montreal, Canada, on radar satellite image processing, she joined Thales Alenia Space in the beginning of 2018. Since then, she has been involved in image processing by Deep Learning for remote sensing applications

Andrés Troya-Galvis: He finished his MsC in 2013 on Computer Science with focus on artificial intelligence and image analysis at the University of Burgundy (France), and his Ph.D in 2016 on Machine Learning and Data Mining applied to Remote Sensing image analysis at the University of Strasbourg (France). In 2017, he was assistant lecturer at INSA Strasbourg and focused his research on Deep Learning techniques for Remote Sensing image classification. He is working as Data Scientist at CCSW/IRD in Thales Alenia Space since January 2018.

Jean-Guy Planès:  Remote sensing, Image Processing and R&D management. He holds a PhD in Electronics and Automatic from Toulouse University, France, 1982. He has been a research engineer in signal processing for biomedical engineering in two French National research institutes (INSERM and CEA) before to join Thales Alenia Space in 1989 as engineer in signal processing for imaging radar. From 1992 to 2013 he was head of an R&D department (up to 20 engineers and 10 PhD’s) for optical and radar image processing and remote sensing applications. He is currently preparing the future satellite ground segments to take the leap on cloud, big data and artificial intelligence technologies.

Mauro Guelfi : Strong international experience in System Engineering and Project Management, with a focus on Space and Radar. Quantitative and analytical profile with a technical ability in acquisition and management of satellite based data, supported by proven experience and knowledge of programme and project management in advanced and complex tasks, and experience on satellite data observation. System Engineer and Mission Operator on X-SAR Program with NASA participation for the STS-59 and STS-68 Space Shuttle Mission. Knowledge and experience in photointerpretation, for quantitative and technical analyses of complex observation and data, applied, inter alia, to assignments for Ministries of Defence and ESA international projects. Further relevant experience in Earth multi-mode observation and satellite systems for the provisioning and elaboration of data for concrete applications. Strong professional background in System Engineering with advanced skills in system and software architecture definition and design of software and hardware platforms.

Antonio Bartolini : Specialist in Neural network, works in Thales Alenia Space Italy both on Neural Network (development and applications) and Mission Planning constraint modelling activity (carried out by developing a Java prototype using open source tools (DROOLS)). Classification of images through a supervised multilayer perceptron neural network.

Developer of both Antennas/ antenna array (to allow communications between Unmanned Aerial Vehicle and Ground Station) and patch array to monitoring the environmental temperature.

Participation in the publication: Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa” published in the magazine: “International Journal of Applied Earth Observations and Geoinformation”.

Alessia Falasco : Currently involved in Thales Alenia Space Italy as Neural Network Specialist. Several years of experience in Artificial Intelligence techniques development for SAR data classification. Participation in projects concerning environmental remote sensing and classification of SAR images, development of artificial intelligence algorithms using Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN), training of supervised and unsupervised Neural Networks. Development of University project on high spatial resolution radar images classification trough contextual analysis, focused on features extraction for land monitoring in spectral domain. Co-Author in "Contextual descriptors and neural networks for scene analysis in VHR SAR images" (A. Falasco, F. Del Frate, M. Picchiani) published in the SPIE Remote Sensing. Also contributor on User Ground Segment in Cosmo Second Generation (CSG) program.

Consortium

CANDELA team is a well-balanced consortium, consisting of seven partners from five European countries, and with strong participation from the industry as encouraged by the Call, being half of the partners well positioned SME’s.