Interacting Weighted Ensemble Kalman Filter applied to Underwater Terrain Aided Navigation

Camille Palmier (1) , Karim Dahia (1) , Nicolas Merlinge (1) , Dann Laneuville (2) , Pierre del Moral (3)

1 DTIS, ONERA, Université Paris Saclay [Palaiseau]
2 Naval Group
3 ASTRAL - Méthodes avancées d’apprentissage statistique et de contrôle

Terrain Aided Navigation (TAN) provides a driftfree navigation approach for Unmanned Underwater Vehicles. This paper focuses on an improved version of the Weighted Ensemble Kalman Filter (WEnKF) to solve the TAN problem. We analyze some theoretical limitations of the WEnKF and derive an improved version which ensures that the asymptotic variance of weights remains bounded. This improvement results in an enhanced robustness to nonlinearities in practice. Numerical results are presented and the robustness is demonstrated with respect to conventional WEnKF, yielding twice as less nonconvergence cases.

Mots clés: Particle filter; UUV; Navigation inertielle; Bathymetry

Domaines: Sciences de l'ingénieur [physics]; Chimie; Informatique [cs]; Mathématiques [math]; Physique [physics]

Camille Palmier, Karim Dahia, Nicolas Merlinge, Dann Laneuville, Pierre del Moral. Interacting Weighted Ensemble Kalman Filter applied to Underwater Terrain Aided Navigation. ACC 2021 - American Control Conference, May 2021, New Orleans / Virtual, United States. ⟨hal-03248265⟩