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UKF Based Nonlinear Filtering Using Minimum Entropy Criterion
IEEE Transactions on Signal Processing, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liu, Yu, Wang, Hong, Hou, Chaohuan
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UKF based robust attitude control for helicopter
Proceedings of the 10th World Congress on Intelligent Control and Automation, 2012In order to handle the model uncertainty and the external disturbance, a robust attitude control method for helicopter robots is proposed in this paper. Unscented Kalman Filter (UKF) and backstepping technique are adopted in the attitude control design. Model-based backstepping control is presented to keep the desired helicopter attitude.
Qi Song, J. D. Han, Zhe Jiang
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Improvement of UKF Algorithm and Robustness Study
2009 International Workshop on Intelligent Systems and Applications, 2009Iterated unscented Kalman filter (IUKF) algorithm has improved the unscented Kalman filter (UKF) and enhanced the performance of filter estimation by using Newton-Raphson iterative equation. This paper improves IUKF algorithm ulteriorly after detailedly analyzing principle of IUKF and its iterative equation, and proposes a new filtering algorithm with ...
Zhong-Kai Mou, Li-Fen Sui
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Gyro fault prediction algorithm based on UKF
2012 International Conference on Image Analysis and Signal Processing, 2012Aimed at the gradient failure of the gyro drift increases, an algorithm based on estimating the angular rate according to the UKF and attitude kinematic equation for gyro fault prediction is presented in this paper. We use quaternion to describe the attitude kinematics equation, and the UKF filter model is created, which takes the satellite attitude ...
Chi Jun, Tian Lu
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Joint Visualization of UKF Tractography Data
2017Tractography methods provide ways to explore white mater in brain. UKF Tractography is a promising one in processing cross fibers and edema regions. In order to get more insight into UKF tractography, we present a joint visualization scheme for UKF tractography data, which integrates and visualizes fiber tracts, diffusion tensors, and multiple tensor ...
Wen Zhao +3 more
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An SLAM algorithm based on improved UKF
2012 24th Chinese Control and Decision Conference (CCDC), 2012Because of using system nonlinear model directly UKF overcomes the shortcomings of the methods such as EKF that they easily introduces truncation errors in the process of lining model .So it is widely used in SLAM problem. Because the square root of filter has the advantages that it can ensure the covariance matrix nonnegative, a square root version of
null Liping Qu +2 more
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Vehicle magnetic field compensation method using UKF
IEEE 2011 10th International Conference on Electronic Measurement & Instruments, 2011Exact measurements of geomagnetic field is very important for navigation. In general, magnetometers fixed on the vehicles are prone to be disturbed by the magnetic field of the vehicles. In order to improve the navigation precision, magnetic field of vehicles must be compensated. In this paper, a new compensation method is proposed. Through analysis of
null Li Ji +4 more
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Phasor estimation considering DC component using UKF
2011 International Conference on Advanced Power System Automation and Protection, 2011Electric power quality is ability of the system to deliver electric power service in high quality so that the end use equipment will operate within its design specifications. Introducing power generation using renewable energy can increase regulations and need for reserves due to its natural intermittency.
Happy Novanda +3 more
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Improved Performance of Adaptive UKF SLAM with Scaling Parameter
2023Simultaneous Localization and Mapping (SLAM) deals with simultaneous mappingand estimates the position of a robot moving in an environment. One of the most commonmethod used in solving the SLAM problem is Extended Kalman Filter (EKF). EKF is anapproach that gives acceptable results in the ideal simulation environment when the systemmodel is known ...
Navruz, Tuğba Selcen +2 more
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Maximum Likelihood Principle Based Adaptive UKF Algorithm
International Journal of Signal Processing, Image Processing and Pattern Recognition, 2016In this paper, we investigate the state estimation problem of nonlinear systems under the condition that the prior statistical characteristic of noise is unknown. An adaptive unscented Kalman filter (UKF) is proposed. In this algorithm, the maximum likelihood principle is applied to establish the log likelihood function with the unknown noise ...
Li Guo, De-gen Huang
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