@ARTICLE{10.21494/ISTE.OP.2018.0280, 

TITLE={A Study of non linear state estimation based on invariant observers}, 
  
AUTHOR={Jean-Philippe Condomines, }, 
	
JOURNAL={Control}, 
	
VOLUME={1}, 

NUMBER={Issue 1}, 
	
YEAR={2017}, 

URL={https://openscience.fr/A-Study-of-non-linear-state-estimation-based-on-invariant-observers}, 
	
DOI={10.21494/ISTE.OP.2018.0280}, 
	
ISSN={2631-4924}, 
	
ABSTRACT={This article presents a study of non linear state estimation based on invariant preserving observer : l’IUKF (Invariant Unscented Kalman Filter ). Several research works on nonlinear invariant observers have been led and provide a geometrical-based constructive method for designing filters such as the IEKF (Invariant Extended Kalman Filter ) wihle preserving the physical properties and systems symmetries. The developed IUKF estimator suggests a systematic approach to determine all the symmetry-preserving correction terms, without requiring any linearization of differential
equations or compatibility condition. The IEKF and IUKF algorithms are compared on academic case of tilt sensor system. The developed IUKF is then used with an aided Inertial Navigation System (INS). The results show promising perpectives and demonstrate that nonlinear state estimation converges on a much bigger set of trajectories than for more traditional approaches.}}