NDLI: Decentralized target positioning and tracking based on a weighted extended Kalman filter for wireless sensor networks

Content Provider	Springer Nature Link
Author	Wang, Chin Liang Wu, Dong Shing
Copyright Year	2013
Abstract	This paper presents a decentralized positioning and tracking method based on recursive weighted least-squares optimization for wireless sensor networks. The proposed algorithm—weighted extended Kalman filter—is derived by minimizing a recursive-in-time objective function and then applying it in an iterative decentralized manner. The target location is calculated iteratively by taking a weighted average of the local estimates based on the participating sensor nodes’ reliability, where a participating sensor node computes the newest location estimate according to its own observation and the most recent local estimate passed from the previous participating sensor node. A convergence analysis is given to show the convergence behavior of the proposed algorithm. To track the target in the network, a message-passing algorithm is proposed for adaptively selecting the participating sensor nodes as the target moves around the area. During each iteration, the current participating sensor node computes the local estimate and passes it on to the next participating sensor node for further processing. The update process is circulated only among the selected participating sensor nodes that surround the target. Computer simulation results show that our proposed algorithm outperforms previous related methods.
Starting Page	1915
Ending Page	1931
Page Count	17
File Format	PDF
ISSN	10220038
Journal	Wireless Networks
Volume Number	19
Issue Number	8
e-ISSN	15728196
Language	English
Publisher	Springer US
Publisher Date	2013-04-04
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Decentralized methods Extended Kalman filters Least-squares optimization Positioning Tracking Wireless sensor networks Communications Engineering, Networks Computer Communication Networks Electrical Engineering Business Information Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems Electrical and Electronic Engineering

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