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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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Comments on “Performance evaluation of UKF-based nonlinear filtering”
Automatica, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yuanxin Wu, Dewen Hu, Xiaoping Hu 0002
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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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Simulation analysis of EKF and UKF implementations in PHD filter
2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC), 2016The probability hypothesis density (PHD) filter is a practical alternative to the optimal Bayesian multi-target filter based on finite set statistics. This paper presents two extensions implementation to nonlinear models in PHD filters, namely the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), and discusses their advantage and ...
Xiaoying Wang, Jiacun Wang
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Performance Analysis of UKF for Nonlinear Problems
2009 Third International Symposium on Intelligent Information Technology Application, 2009Unscented Kalman filter (UKF) is a class of nonlinear filtering methods based on unscented transform within the Kalman filter framework. It is in light of the intuition that to approximate a probability distribution by a set of deterministic samples is easier than to approximate an arbitrary nonlinear transform.
Guanglin Li, Fuming Sun, Na Cheng
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Study on expansion and non-expansion of UKF
2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC), 2011It is usually accepted that UKF can be used in the form of state non-expansion when noise is additive, in order to prove it incorrect, we made use of scaled symmetric set unscented transformation to deduce and explain the difference in the situation of complicated additive noise model, theory deduction results indicated there were differences between ...
Li Heng, Zhang Jing-yuan, Luo Xuan
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An adaptive UKF with noise statistic estimator
2009 4th IEEE Conference on Industrial Electronics and Applications, 2009The normal unscented Kalman filter (UKF) suffers from performance degradation and even divergence while mismatch between the noise distribution assumed to be known as a priori by UKF and the true ones in a real system. In order to improve the performance of the UKF with uncertain or timevarying noise statistic, a novel adaptive UKF with noise statistic
null Lin Zhao, null Xiaoxu Wang
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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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2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2016
In the development of advanced driver-assist systems (ADAS) for lane-keeping, one important design objective is to appropriately share the steering control with the driver. Hence, the steering behavior of the driver must be well known beforehand. This paper adopts the well-known two-point visual driver model to characterize the steering behavior of the
Changxi You +2 more
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In the development of advanced driver-assist systems (ADAS) for lane-keeping, one important design objective is to appropriately share the steering control with the driver. Hence, the steering behavior of the driver must be well known beforehand. This paper adopts the well-known two-point visual driver model to characterize the steering behavior of the
Changxi You +2 more
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A human motion estimation method based on GP-UKF
2014 IEEE International Conference on Information and Automation (ICIA), 2014A novel human motion estimation method is presented in this paper. The motion of the human is estimated by an Unscented Kalman filter (UKF), in which a nonlinear dynamic model is used to predict trajectory of human. This dynamic model is obtained from sample data by using Gaussian Process (GP) regression.
Ziyou Wang +3 more
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