Combining Kalman Filtering with ZigBee Protocol to Improve Localization in Wireless Sensor Network. (21st March 2013)
- Record Type:
- Journal Article
- Title:
- Combining Kalman Filtering with ZigBee Protocol to Improve Localization in Wireless Sensor Network. (21st March 2013)
- Main Title:
- Combining Kalman Filtering with ZigBee Protocol to Improve Localization in Wireless Sensor Network
- Authors:
- El Madani, Bouchra
Yao, Anne Paule
Lyhyaoui, Abdelouahid - Other Names:
- Brandl M. Academic Editor.
Song A. Academic Editor. - Abstract:
- Abstract : 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 (δ ) 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.
- Is Part Of:
- ISRN sensor networks. Volume 2013(2013)
- Journal:
- ISRN sensor networks
- Issue:
- Volume 2013(2013)
- Issue Display:
- Volume 2013, Issue 2013 (2013)
- Year:
- 2013
- Volume:
- 2013
- Issue:
- 2013
- Issue Sort Value:
- 2013-2013-2013-0000
- Page Start:
- Page End:
- Publication Date:
- 2013-03-21
- Subjects:
- Sensor networks -- Periodicals
Wireless sensor networks -- Periodicals
Sensor networks
Wireless sensor networks
Periodicals
006.25 - Journal URLs:
- https://www.hindawi.com/journals/isrn/contents/isrn.sensor.networks/ ↗
- DOI:
- 10.1155/2013/252056 ↗
- Languages:
- English
- ISSNs:
- 2090-7745
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10825.xml