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2007
IEEE

An Adaptive Location Estimator Based on Kalman Filtering for Wireless Sensor Networks

10 years 1 months ago
An Adaptive Location Estimator Based on Kalman Filtering for Wireless Sensor Networks
—In this paper, we present a positioning and tracking scheme based on adaptive weighted interpolation and Kalman filtering for wireless sensor networks. The proposed positioning method formulates location estimation as a weighted least squares problem by taking weights based on the reliability of distance estimation. This method can be realized in an iterative, decentralized manner to improve both bandwidth and energy efficiencies. To improve the location accuracy, a Kalman filter is employed at the central server to track variations of the location estimate computed from the proposed positioning method. As compared with a previous positioning approach based on the projection onto convex sets, the proposed scheme has faster convergence speed and better location accuracy. Computer simulation results show that more than 90 percent of the location estimates computed from the proposed approach have error distances less than 2.5 meters. Keywords-decentralized manner; Kalman filtering; pos...
Chin-Liang Wang, Yih-Shyh Chiou, Yu-Sheng Dai
Added 04 Jun 2010
Updated 04 Jun 2010
Type Conference
Year 2007
Where VTC
Authors Chin-Liang Wang, Yih-Shyh Chiou, Yu-Sheng Dai
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