Paper Info
Title
Localization Performance Evaluation of Extended Kalman Filter in Wireless Sensors Network.
Abstract
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.
Year
DOI
Venue
2014
10.1016/j.procs.2014.05.405
Procedia Computer Science
Keywords
Field
DocType
Wireless Sensors Network,Positioning,Tracking,Extended Kalman Filter
Data mining,Extended Kalman filter,Wireless,Iterative and incremental development,Computer science,Kalman filter,Real-time computing,Radio frequency,Multilateration,Invariant extended Kalman filter,Linearization
Conference
Volume
ISSN
Citations 
32
1877-0509
4
PageRank 
References 
Authors
0.43
3
4
Name
Order
Citations
PageRank
Rafiullah Khan11579.66
Sarmad Ullah Khan216114.20
Shahid A. Khan3315.11
Mohammad Usman Ali Khan440.43