Kalman vs H∞ filter in terms of convergence and accuracy: Application to carrier frequency offset estimation
Héctor Poveda, Eric Grivef, Guillaume Ferré, Nicolai D. Christov · European Signal Processing Conference · 2012
H ∞ filtering is more and more used in the field of recursive estimation in signal processing. The purpose of this communication is to compare Kalman filtering and H ∞ filtering by considering their Ricatti-type equations. Our contribution is twofold: firstly, we show that the H ∞ filter can be seen as a Kalman filter with a model-noise covariance matrix that depends on the noise attenuation level and varies in time. Hence, this can explain the convergence properties of the H ∞ filter when estimating parameters. The convergence and accuracy properties of both Kalman and H ∞ filters are then illustrated by the estimation of a carrier frequency offset in a mobile communication system.