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

Abstract : 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.
Type de document :
Communication dans un congrès
2017 18th International Radar Symposium (IRS), Jun 2017, Prague, Czech Republic. IEEE, 2017 18th International Radar Symposium (IRS), 〈http://www.dgon-irs.org/index.php?id=69〉. 〈10.23919/IRS.2017.8008156〉
Liste complète des métadonnées

Littérature citée [16 références]  Voir  Masquer  Télécharger

https://hal-mines-paristech.archives-ouvertes.fr/hal-01692475
Contributeur : Marion Pilté <>
Soumis le : jeudi 25 janvier 2018 - 11:01:13
Dernière modification le : lundi 12 novembre 2018 - 10:59:15
Document(s) archivé(s) le : jeudi 24 mai 2018 - 22:49:10

Fichier

IRS_17_abstract.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

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. IEEE, 2017 18th International Radar Symposium (IRS), 〈http://www.dgon-irs.org/index.php?id=69〉. 〈10.23919/IRS.2017.8008156〉. 〈hal-01692475〉

Partager

Métriques

Consultations de la notice

146

Téléchargements de fichiers

75