An Innovative Nonlinear Filter for Radar Kinematic Estimation of Maneuvering Targets in 2D

Marion Pilté (1, 2) , Silvère Bonnabel (2) , Frédéric Barbaresco (3)

1 Thales Air Systems
2 CAOR - Centre de Robotique
3 Thales Research and Technology [Palaiseau]

In this paper we consider the problem of tracking a target in a 2D space whose model is based on a constant velocity assumption (up to a process noise) in the Frenet-Serret frame (or intrinsic coordinates). This model is particularly suited to straight lines and coordinated turn motions. Then, we adapt the Invariant Extended Kalman Filter (I-EKF), as in [1], a novel variant of the EKF on Lie groups, to suit this dynamical model. Numerical experiments inspired by real fighter trajectories confirm the validity of our approach.

Domaines: Mathématiques [math]; Mathématiques appliquées

Marion Pilté, Silvère Bonnabel, Frédéric Barbaresco. An Innovative Nonlinear Filter for Radar Kinematic Estimation of Maneuvering Targets in 2D. 2017 18th International Radar Symposium (IRS), Jun 2017, Prague, Czech Republic. ⟨10.23919/IRS.2017.8008156⟩. ⟨hal-01692475⟩