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    NTHUR > College of Electrical Engineering and Computer Science > Department of Electrical Engineering > EE Journal / Magazine Articles  >  Reduced-complexity scheme using alpha-beta filtering for location tracking

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    Title: Reduced-complexity scheme using alpha-beta filtering for location tracking
    Authors: Yih-Shyh Chiou;Chin-Liang Wang;Sheng-Cheng Yeh
    Teacher: 王晉良
    Date: 2011
    Publisher: Institution of Engineering and Technology
    Relation: IET COMMUNICATIONS, Institution of Engineering and Technology, Volume 5, Issue 13, SEP 5 2011, Pages 1806-1813
    Keywords: FUTURE
    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.
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    Appears in Collections:[Department of Electrical Engineering] EE Journal / Magazine Articles
    [Institute of Communications Engineering] COM Journal / Magazine Articles
    [Computer and Communication Research Center ] CCRC Journal / Magazine Articles

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