Dey, Subhrakanti and Leong, Alex S. and Evans, Jamie S. (2009) Kalman filtering with faded measurements. Automatica, 45 (10). ISSN 0005-1098

Preview

Download (2MB) | Preview

Abstract

This paper considers a sensor network where single or multiple sensors amplify and forward their measurements of a common linear dynamical system (analog uncoded transmission) to a remote fusion center via noisy fading wireless channels. We show that the expected error covariance (with respect to the fading process) of the time-varying Kalman filter is bounded and converges to a steady state value, based on some earlier results on asymptotic stability of Kalman filters with random parameters. More importantly, we provide explicit expressions for sequences which can be used as upper bounds on the expected error covariance, for specific instances of fading distributions and scalar measurements (per sensor). Numerical results illustrate the effectiveness of these bounds.

Item Type:	Article
Keywords:	Fading channels; Kalman filtering; Sensor networks; Stability;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	14421
Identification Number:	https://doi.org/10.1016/j.automatica.2009.06.025
Depositing User:	Subhrakanti Dey
Date Deposited:	11 May 2021 14:32
Journal or Publication Title:	Automatica
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads