Statistical analysis of wireless sensor network Gaussian range estimation errors

• Published in: IET wireless sensor systems 2013-03, Vol.3 (1), p.57-68
• Main Authors: Rasool, Imtiaz, Kemp, Andrew H
• Format: Article
• Language: English
• Subjects: Algorithms; Anderson–Darling test; Applied sciences; chi‐squared test; cluttered environment; computer generated data; Computer simulation; Detection, estimation, filtering, equalization, prediction; empirical cumulative distribution function plotting; Error analysis; Error detection; estimation theory; Exact sciences and technology; Gaussian; Gaussian distributed; Gaussian distribution; Gaussianity assumption; GOF statistical analysis; GOF techniques; graphical goodness‐of‐fit technique; IEEE 802.15.4 compliant WSN test‐bed; indoor communication; indoor environment; Information, signal and communications theory; kurtosis test; linear correlation coefficient test; non‐line‐of‐sight propagation conditions; numerical goodness‐of‐fit technique; probability density function plotting; quantile–quantile plotting; range filtration algorithm; REE; Remote sensors; RFA; Services and terminals of telecommunications; Signal and communications theory; Signal, noise; skewness test; Statistical analysis; statistical testing; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Telemetry. Remote supervision. Telewarning. Remote control; time‐of‐flight ranging; Wireless networks; wireless sensor network Gaussian range estimation errors; wireless sensor networks; WSN localisation; Zigbee
• ISSN: 2043-6386; 2043-6394; 2043-6394
• DOI: 10.1049/iet-wss.2012.0073

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 (A2) test and chi-squared (χ2) 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 A2 test, it filters out the range estimates with high errors.