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An adaptive location estimator based on alpha-beta filtering for wireless sensor networks
Conference paper

An adaptive location estimator based on alpha-beta filtering for wireless sensor networks

Chin-Liang Wang, Yih-Shyh Chiou and Yu-Sheng Dai
IEEE Wireless Communications and Networking Conference, WCNC, pp.3287-3292
2007

Abstract

Alpha-beta filtering Kalman filtering Positioning Tracking Weighted interpolation Wireless sensor network
This paper presents a new scheme for positioning and tracking mobile nodes based on adaptive weighted interpolation and Alpha-Beta (α-β) Altering in wireless sensor networks. The proposed positioning method formulates location estimation as a weighted least squares problem, which can be solved in an iterative, decentralized manner. With such estimated location information, an α-β tracking algorithm is further employed at a central processor to improve the location accuracy. As compared with the Kaiman Altering approach, the proposed α-β tracking method achieves reasonably good performance with much lower computational complexity and no need of exact information about the state and measurement noise parameters. Computer simulation results show that more than 90 percent of the estimated locations have error distances less than 2.5 meters. © 2007 IEEE.

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