DocumentCode
2494475
Title
Node self-positioning in wireless sensor networks using graded estimation and Taylor-Series algorithm
Author
Hu, Yanzhi ; Ma, Dawei ; Tian, Tian
Author_Institution
Chongqing Commun. Inst., Chongqing
fYear
2008
fDate
25-27 June 2008
Firstpage
6711
Lastpage
6714
Abstract
Node self-positioning is a fundamental and crucial issue for sensor network operation, management and applications. In this paper, an efficient location method is proposed based on received signal strength information (RSSI). We first utilize the known-location nodes (anchor nodes) to locate the unknown-location nodes in a single-hop range, and the estimated nodes are regarded as new anchor nodes in the following position estimation. Similar process is carried out for the rest of the unknown-location nodes based on more anchor nodes. In order to overcome the diffusion effect of the accumulative error introduced by new anchor nodes, Taylor-series expansion method is applied to optimize the estimated values. It is shown the method mentioned in the paper enhances positioning accuracy of self-localization and reduces the dependency on priori knowledge of node coordinates in wireless sensor networks (WSNs).
Keywords
estimation theory; telecommunication network management; wireless sensor networks; Taylor-series expansion method; graded estimation; location method; node self-positioning; position estimation; received signal strength information; sensor network management; wireless sensor networks; Automation; Communication system operations and management; Costs; Density measurement; Intelligent control; Intelligent sensors; Optimization methods; Sensor systems; Ultrasonic variables measurement; Wireless sensor networks; Self-positioning; Taylor-Series; location method; sensor network;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4593945
Filename
4593945
Link To Document