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

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2 Author(s)
Jieyang Yi ; Sch. of Commun. & Inf. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China ; Liang Zhou

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.

Published in:

Computational Problem-Solving (ICCP), 2011 International Conference on

Date of Conference:

21-23 Oct. 2011

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