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Localization performance evaluation of extended kalman filter in wireless sensors network
Khan, Rafiullah; Khan, Sarmad Ullah; Khan, Shahid Ahmed; Khan, Mohammad Usman Ali
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
This paper evaluates the positioning and tracking performance of Extended Kalman Filter (EKF) in wireless sensors network. The EKF is a linear approximation of statistical Kalman Filter (KF) and has the capability to work efficiently in non-linear systems. The EKF is based on an iterative process of estimating current state information from the previously estimated state. Its working is based on the linearization of observation model around the mean of current state information. The EKF has small computation complexity and requires low memory compared to other Bayesian algorithms which makes it very suitable for low powered mobile devices. This paper evaluates the localization and tracking performance of EKF for (i) Position (P) model, (ii) Position-Velocity (PV) model and (iii) Position-Velocity-Acceleration (PVA) model. The EKF processes distance measurements from cricket sensors that are acquired through time difference of arrival between ultrasound and Radio Frequency (RF) signals. Further, localization performance under varying number of beacons/sensors is also evaluated in this paper. © 2014 Published by Elsevier B.V.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
Wireless communication systems
Extended Kalman filter
Positioning
Tracking
Wireless sensors network
Comunicació sense fil, Sistemes de
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Elsevier
         

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