Kriging-based estimation of time derivatives via FIR filtering

Author

Marzat, J. ; Piet-Lahanier, H. ; Walter, Eric

Author_Institution

ONERA - The French Aerosp. Lab., Palaiseau, France

fYear

2013

fDate

22-25 Sept. 2013

Firstpage

1

Lastpage

6

Abstract

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.

Keywords

FIR filters; Kalman filters; missile guidance; statistical analysis; target tracking; FIR filtering; Kalman filtering; constant coefficients; differentiator; finite impulse response filter; kriging-based estimation; kriging-based filter; maneuvering target acceleration estimation; missile guidance; noisy signal; regularly spaced samples; target tracking; time derivative estimation; Acceleration; Estimation; Finite impulse response filters; Kalman filters; Missiles; Noise measurement; Tuning; FIR filtering; Kriging; noisy data; numerical differentiation; target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on

Conference_Location

Southampton

ISSN

1551-2541

Type

conf

DOI

10.1109/MLSP.2013.6661940

Filename

6661940