A Spherical Simplex Unscented Rauch-Tung Striebel Smoother for a Vehicle Localization Problem

Z., Zolkafli and Saifudin, Razali (2017) A Spherical Simplex Unscented Rauch-Tung Striebel Smoother for a Vehicle Localization Problem. Advanced Science Letters, 23 (6). pp. 5556-5560. ISSN 1936-6612

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The unscented Kalman filter (UKF) has become relatively a new technique used in a number of nonlinear estimation problems to overcome the limitation of Taylor series linearization. It uses a deterministic sampling approach known as sigma points to propagate nonlinear systems and has been discussed in many literature. However, a nonlinear smoothing problem has received less attention than the filtering problem. Therefore, in this article an unscented smoother based on Rauch-Tung-Striebel form is examined for discrete-time dynamic systems. It has advantages available in unscented transformation over approximation by Taylor expansion as well as its benefit in derivative free. In addition, new sampling technique known as a spherical simplex has been introduced and evaluated. To show the effectiveness of the proposed method, the unscented smoother is implemented and evaluated through a vehicle localization problem

Item Type: Article
Uncontrolled Keywords: Spherical simplex unscented transformation; Rauch-Tung-Striebel smoother; Vehicle localization
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 28 Aug 2017 06:29
Last Modified: 28 Aug 2017 06:29
URI: http://umpir.ump.edu.my/id/eprint/14035
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