Combining Kalman Filtering with ZigBee Protocol to Improve Localization in Wireless Sensor Network | Zendy

Bouchra El Madani | Zendy; Anne Paule Yao | Zendy; Abdelouahid Lyhyaoui | Zendy

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Combining Kalman Filtering with ZigBee Protocol to Improve Localization in Wireless Sensor Network

Author(s) -

Bouchra El Madani,

Anne Paule Yao,

Abdelouahid Lyhyaoui

Publication year - 2013

Publication title -

isrn sensor networks

Language(s) - English

Resource type - Journals

ISSN - 2090-7745

DOI - 10.1155/2013/252056

Subject(s) - kalman filter , wireless sensor network , protocol (science) , convergence (economics) , computer science , ranging , process (computing) , real time computing , wireless , power consumption , scheme (mathematics) , power (physics) , transformation (genetics) , algorithm , computer network , artificial intelligence , mathematics , telecommunications , medicine , mathematical analysis , physics , alternative medicine , biochemistry , chemistry , pathology , quantum mechanics , economics , gene , economic growth , operating system

We propose a low-cost and low-power-consumption localization scheme for ZigBee-based wireless sensor networks (WSNs). Our design is based on the link quality indicator (LQI)—a standard feature of the ZigBee protocol—for ranging and the ratiometric vector iteration (RVI)—a light-weight distributed algorithm—modified to work with LQI measurements. To improve performance and quality of this system, we propose three main ideas: a cooperative approach, a coefficient delta () to regulate the speed of convergence of the algorithm, and finally the filtering process with the extended Kalman filter. The results of experiment simulations show acceptable localization performance and illustrate the accuracy of this method.

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