Kriging-based estimation of time derivatives via FIR filtering

Julien Marzat (1, 2) , Hélène Piet-Lahanier (1) , Eric Walter (3)

1 ONERA - The French Aerospace Lab [Palaiseau]
2 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
3 L2S - Laboratoire des signaux et systèmes

Time derivatives of a noisy signal are estimated using a Kriging-based filter. Under the assumption of regularly spaced samples, the resulting differentiator turns out to be a finite impulse response filter (FIR) with constant coefficients. The method is employed to estimate the acceleration of a maneuvering target in the context of missile guidance and the results are compared with those obtained with conventional Kalman filtering.

Mots clés: noisy data; Kriging; numerical differentiation; FIR filtering; target tracking

Domaines: Automatique / Robotique; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Julien Marzat, Hélène Piet-Lahanier, Eric Walter. Kriging-based estimation of time derivatives via FIR filtering. IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Sep 2013, Southampton, United Kingdom. ⟨10.1109/mlsp.2013.6661940⟩. ⟨hal-00877181⟩