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Comments on “Performance evaluation of UKF-based nonlinear filtering”
Automatica, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Yuanxin, Hu, Dewen, Hu, Xiaoping
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Development of Extended MVEM based UKF estimators
2011 Annual IEEE India Conference, 2011Mean Value Engine Models (MVEM) have been used to model the averaged dynamics of an automobile engine system for automotive control and fault diagnosis. For these purposes, it is common to estimate states of interest given noisy measurements using state observers.
Jonathan Vasu +2 more
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UKF-Based Image Filtering and 3D Reconstruction
2019In the global world of robotics, robots have missions to achieve interactively with human environments and online learning. Practically, for null error of a robot’s achievement, robotics systems should be provided with minimal certain information in advance. This is crucial for any high-performance robotics systems.
Abdulkader Joukhadar +2 more
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ANFIS Based UKF-SLAM Path Planning Method
2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2019Reducing error in each step of robot motion is one of the important issue in the Simultaneous Localization and Mapping algorithms. Hence, an accurate estimation method can enhance the behavior of the SLAM algorithm in the unknown environment. A hybrid estimation method is presented in this work which is consisted of ANFIS with Unscented Kalman Filter ...
Salman Sahib M. Gharib, Parvaneh Esmaili
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Performance evaluation of UKF-based nonlinear filtering
Automatica, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiong, K., Zhang, H. Y., Chan, C. W.
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Nonlinear Target Identification and Tracking Using UKF
2007 IEEE International Conference on Granular Computing (GRC 2007), 2007In this paper, we implemented target identification algorithm using Dempster Shafer theory (DST) and tracking algorithm using extended Kalman filter (EKF) and unscented Kalman filter (UKF). A tracking filter is developed and simulated based on UKF to track nonlinear, ballistic and reentry targets.
KHAIRNAR, DG +3 more
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UKF Fusion Estimation for Indoor RFID Tracking
Applied Mechanics and Materials, 2013Radio frequency identification (RFID) can effectively get the accurate location information for indoor tracking system. The readers cant be placed at any position in the practical system. the reader would be more intensive at some places, where will obtain measurements from several readers, while the reader will be placed less at others place, where ...
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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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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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Effective fault diagnosis based on strong tracking UKF
Aircraft Engineering and Aerospace Technology, 2011PurposeThe purpose of this paper is to address the flaws of traditional methods and fulfil the special fault‐tolerant re‐entry navigation requirements of reusable boost vehicle (RBV).Design/methodology/approachA kind of improved estimation method based on strong tracking unscented Kalman filter (STUKF) is put forward.
Pengxin Han, Rongjun Mu, Naigang Cui
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