Statistical analysis of wireless sensor network Gaussian range estimation errors. Issue 1 (1st March 2013)

• Record Type: Journal Article
• Authors: Rasool, Imtiaz; Kemp, Andrew H.
• Is Part Of: IET wireless sensor systems. Volume 3:Issue 1(2013)
• Page Start: 57
• Page End: 68
• Publication Date: 2013-03-01
• Subjects: estimation theory -- Gaussian distribution -- indoor communication -- statistical testing -- wireless sensor networks -- Zigbee; wireless sensor network Gaussian range estimation errors -- WSN localisation -- time‐of‐flight ranging -- REE -- indoor environment -- cluttered environment -- Gaussianity assumption -- computer generated data -- IEEE 802.15.4 compliant WSN test‐bed -- non‐line‐of‐sight propagation conditions -- graphical goodness‐of‐fit technique -- numerical goodness‐of‐fit technique -- GOF techniques -- quantile–quantile plotting -- empirical cumulative distribution function plotting -- probability density function plotting -- linear correlation coefficient test -- kurtosis test -- skewness test -- Anderson–Darling test -- chi‐squared test -- GOF statistical analysis -- Gaussian distributed -- range filtration algorithm -- RFA; Wireless sensor networks -- Periodicals; 681.2
• DOI: 10.1049/iet-wss.2012.0073
• Languages: English
• ISSNs: 2043-6386

Abstract

Abstract : Wireless sensor network (WSN) localisation has attracted significant research interest. The quality of time‐of‐flight ranging when used as the basis of localisation, has a direct impact on precision and accuracy. Recently significant attention has been devoted to modelling and analysis of range estimation error (REE) in indoor and cluttered environments. A Gaussianity assumption for the distribution of REE is a common practice in the literature. The motivation of this study is to analyse this assumption. To scrutinise this, rather than relying on computer generated data, a real IEEE 802.15.4 compliant WSN test‐bed is used for collecting ranging data, covering outdoor and indoor environments for both line‐of‐sight and non‐line‐of‐sight propagation conditions. The distribution of REE is analysed using both graphical and numerical goodness‐of‐fit (GOF) techniques, that is, quantile–quantile plotting, empirical cumulative distribution function plotting, probability density function plotting, linear correlation coefficient ( γ ) test, kurtosis ( K ) test, skewness ( S ) test, Anderson–Darling ( A 2 ) test and chi‐squared ( χ 2 ) test. The GOF statistical analysis of the experimental results suggest that REE is not Gaussian distributed. A novel means of enhancement called the range filtration algorithm (RFA) is proposed. The RFA is based on the A 2 test, it filters out the range estimates with high errors.