CURRENT RESEARCH ACTIVITIES
Enhanced planetary sounding radar data assimilation using probabilistic forward models
Project proposal for spaceborn planetary sounding radar data analysis.
Short machine learning studies
-Study based on random resampling to derive a new mapping used to perform Bayesian learning of integral transforms of an unknown probability distribution.
-Additional study which investigates the link between kernel methods and quantum mechanics
LiDAR SLAM for exploration robotics using probabilistic forward models
This work uses a new mapping algorithm to derive efficient particle filter SLAM algorithms for robust SLAM in exploration robotics applications.
Planetary sounding using multistatic radar
This work aims at assessing the ability to recover information on planetary body interior using multistatic radar. More specifically, the idea is to investigate requirements needed on instrument parameters such as orbitography, antenna orientation, antenna gain, environmental radiations and shape model for proper data inversion (tomography or full-waveform inversion).