Journal ArticleDOI
Navigation Integration Using the Fuzzy Strong Tracking Unscented Kalman Filter
Dah-Jing Jwo,Shih-Yao Lai +1 more
TLDR
A novel scheme called the fuzzy strong tracking unscented Kalman filter (FSTUKF) is presented where the Fuzzy Logic Adaptive System (FLAS) is incorporated for determining the softening factor.Citations
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Dissertation
Unscented Kalman Filterの計測への応用に関する研究
TL;DR: In this article, the authors consider a robot with two drive wheels, of radius r on an axle of length d, rotating at different velocities: the right wheel at a velocity of φRt and the left at a speed of ΆLt.
Journal ArticleDOI
A new direct filtering approach to INS/GNSS integration
TL;DR: A refined strong tracking unscented Kalman filter (RSTUKF) is developed to enhance the UKF robustness against kinematic model error and maintains the optimal UKF estimation in the absence of kinematics model error.
Journal ArticleDOI
Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages
TL;DR: Comparison results indicate that the proposed model combined with STKF/WNN algorithms can effectively provide high accurate corrections to the standalone INS during GPS outages.
Journal ArticleDOI
Networked Strong Tracking Filtering with Multiple Packet Dropouts: Algorithms and Applications
TL;DR: It is shown that the proposed NSTF is capable of providing satisfactory estimation results even in the presence of system parameter perturbations and/or unknown system inputs and the effectiveness and applicability of the proposed filtering techniques are shown.
References
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Journal ArticleDOI
Fuzzy identification of systems and its applications to modeling and control
T. Takagi,Michio Sugeno +1 more
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Book
Applied Optimal Estimation
TL;DR: This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation, and the theory and practice of optimal estimation is presented.
Proceedings ArticleDOI
The unscented Kalman filter for nonlinear estimation
Eric A. Wan,R. van der Merwe +1 more
TL;DR: The unscented Kalman filter (UKF) as discussed by the authors was proposed by Julier and Uhlman (1997) for nonlinear control problems, including nonlinear system identification, training of neural networks, and dual estimation.
Journal ArticleDOI
A new method for the nonlinear transformation of means and covariances in filters and estimators
TL;DR: A new approach for generalizing the Kalman filter to nonlinear systems is described, which yields a filter that is more accurate than an extendedKalman filter (EKF) and easier to implement than an EKF or a Gauss second-order filter.
Book
introduction to random signals and applied kalman filtering
TL;DR: In this paper, the Discrete Kalman Filter (DFL) is used for smoothing and prediction linearization in the Global Positioning System (GPS) and a case study is presented.
Related Papers (5)
Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise: application to parameter estimation and empirical robustness analysis
D. H. Zhou,Paul M. Frank +1 more