NDLI: Detecting Outlier Measurements Based on Graph Rigidity for Wireless Sensor Network Localization

Content Provider	IEEE Xplore Digital Library
Author	Zheng Yang Chenshu Wu Tao Chen Yiyang Zhao Wei Gong Yunhao Liu
Copyright Year	1967
Abstract	A majority of localization approaches for wireless sensor networks rely on the measurements of internode distance. Errors are inevitable in distance measurements, and we observe that a small number of outliers can drastically degrade localization accuracy. To deal with noisy and outlier ranging results, a straightforward method, known as triangle inequality, has often been employed in previous studies. However, triangle inequality has its own limitations that make it far from accurate and reliable. In this paper, we first analyze how much information is needed to identify outlier measurements. Applying the rigidity theory, we propose the concept of verifiable edges and derive the conditions for an edge to be verifiable. On this basis, we design a localization approach with outlier detection, which explicitly eliminates ranges with large errors before location computation. Considering the entire network, we define verifiable graphs in which all edges are verifiable. If a wireless network meets the requirements of graph verifiability, it is not only localizable but outlier resistant as well. Extensive simulations are conducted to examine the effectiveness of the proposed approach. The results show remarkable improvement in location accuracy by sifting outliers.
Sponsorship	IEEE Vehicular Technology Society
Starting Page	374
Ending Page	383
Page Count	10
File Size	1080509
File Format	PDF
ISSN	00189545
Volume Number	62
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Distance measurement Image edge detection Accuracy Noise measurement Noise Wireless sensor networks Hardware wireless sensor networks Localization outlier detection verifiability
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Automotive Engineering Computer Networks and Communications Electrical and Electronic Engineering Aerospace Engineering

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