NDLI: Enhanced location algorithm with received-signal-strength using fading Kalman filter in wireless sensor networks

Content Provider	IEEE Xplore Digital Library
Author	Jieyang Yi Liang Zhou
Copyright Year	2011
Description	Author affiliation: IEEE Conference Publishing, School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu SiChuan 611731, China (Jieyang Yi; Liang Zhou)
Abstract	As one of the most significant technology in wireless sensor networks (WSN), localization has drawn much attention. In this paper, received signal strength (RSS) values are used as the indicator of the distance between blind node and reference nodes. The position of blind node is calculated via multilateration algorithm (MA). In order to improve the accuracy, Kalman filter (KF) is utilized to estimate the actual position. Due to the flaw of the model, divergence phenomenon occurs when the moving direction of blind node changes. Therefore, Kalman filter algorithm performs badly in location and tracking. However, a novel method is proposed by using fading Kalman filter (FKF) and finally improves the accuracy of location.
Starting Page	458
Ending Page	461
File Size	160680
Page Count	4
File Format	PDF
ISBN	9781457706028
e-ISBN	9781457706035
e-ISBN	9781457706011
DOI	10.1109/ICCPS.2011.6089930
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless communication Wireless sensor networks Accuracy Wireless sensor networks (WSN) Received signal strength (RSS) Kalman filter (KF) Trajectory Kalman filters Mathematical model Multilateration algorithm (MA) Fading Kalman filter (FKF)
Content Type	Text
Resource Type	Article

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