Reduced-complexity scheme using alpha-beta filtering for location tracking

NCUIR > Research Center > Center for Space and Remote Sensing Research > journal & Dissertation > Item 987654321/50640

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/50640

Title:	Reduced-complexity scheme using alpha-beta filtering for location tracking
Authors:	Chiou,YS;Wang,CL;Yeh,SC
Contributors:	太空及遙測研究中心
Keywords:	FUTURE
Date:	2011
Issue Date:	2012-03-27 17:49:43 (UTC+8)
Publisher:	國立中央大學
Abstract:	This study presents an efficient location tracking algorithm to reduce the computational complexity of the conventional Kalman filtering (KF) algorithm. In the proposed training and tracking scheme, the authors replace the decision mode of the KF algorithm with an alpha-beta (alpha-beta) algorithm to avoid repeatedly calculating the Kalman gain. After the mode with alpha-beta - tracking, the exact information of the state and measurement noise parameters used in the KF algorithm is not required. Using the inherent fixed-coefficient feature of alpha-beta filtering, the location information between the prediction phase and correction phase is efficiently cycled, thus simplifying implementation of the KF approach. Under a stationary environment, numerical simulations show that the proposed training and tracking approach not only can achieve the location accuracy close to the KF scheme but has much lower computational complexity.
Relation:	IET COMMUNICATIONS
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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