DocumentCode
1849985
Title
A New Node Self-Localization Algorithm Based RSSI for Wireless Sensor Networks
Author
Feng Cheng-Xu ; Liu Zhong
Author_Institution
Electron. Eng. Coll., Naval Univ. of Eng., Wuhan, China
fYear
2013
fDate
21-23 June 2013
Firstpage
1616
Lastpage
1619
Abstract
In various applications of wireless sensor network, sensor nodes must know their location information to fulfill further assignments such as target real-time monitoring and target tracking. In this paper, a new node self-localization algorithm based on the received signal strength indicator (RSSI) is proposed. The new algorithm takes both triangle centroid localization algorithm (ACLA) and approximate point-in-triangulation test (APIT) algorithm into consideration. In this algorithm, the triangle centroid localization model is improved by optimizing the coefficient of the weighted centroid. And in order to solve non-idealized triangle problem, we make use of APIT to select idealized triangle for localization. The simulation results show that the improved algorithm has less localization error compared to the existing RSSI algorithm.
Keywords
approximation theory; target tracking; wireless sensor networks; APIT; RSSI; approximate point-in-triangulation test algorithm; localization error; node self-localization algorithm; nonidealized triangle problem; real-time monitoring; received signal strength indicator; self-localization algorithm; target tracking; triangle centroid localization algorithm; triangle centroid localization model; weighted centroid; wireless sensor networks; Approximation algorithms; Educational institutions; Mathematical model; Robot sensing systems; Simulation; Target tracking; Wireless sensor networks; approximate point-in-triangulation test (APIT); node self-localization; received signal strength indicator (RSSI); wireless sensor networks (WSN);
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location
Shiyang
Type
conf
DOI
10.1109/ICCIS.2013.423
Filename
6643341
Link To Document