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A Modified Adaptive Square-root Cubature Kalman Filter for GNSS/INS Integration
ION GNSS+, The International Technical Meeting of the Satellite Division of The Institute of Navigation, 2018In the GNSS/INS integrated navigation system, the filtering accuracy of Square-root Cubature Kalman Filter (SCKF) will reduce when the measurement noise statistics is not precisely known. To solve this problem, a Modified Adaptive SCKF (MASCKF) method is proposed.
Zhe Yue +4 more
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Design of adaptive robust square-root cubature Kalman filter with noise statistic estimator
Applied Mathematics and Computation, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Liqiang +4 more
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Maneuvering Target Tracking Based on Adaptive Square Root Cubature Kalman Filter Algorithm
2012Concerning low accuracy even divergence of maneuvering target tracking due to inaccurate tracking model and statistical property, an adaptive Square Root Cubature Kalman Filter (SCKF) is proposed based on the standard SCKF and modified Sage-Husa estimator.
Sisi Wang, Lijun Wang
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The application of square-root cubature Kalman filter in SLAM for underwater robot
2017 Chinese Automation Congress (CAC), 2017For simultaneous localization and mapping(SLAM) of underwater robots, the extended Kalman filter algorithm has the problems of slow convergence rate, low accuracy and poor numerical stability, and square root cubature Kalman filter SLAM algorithm (SRCKF-SLAM) for mobile robots is designed according to cubature Kalman filter (CKF) principle.
Xun Li +5 more
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Multi-sensor hybrid fusion algorithm based on adaptive square-root cubature Kalman filter
Journal of Marine Science and Application, 2013In the normal operation condition, a conventional square-root cubature Kalman filter (SRCKF) gives sufficiently good estimation results. However, if the measurements are not reliable, the SRCKF may give inaccurate results and diverges by time. This study introduces an adaptive SRCKF algorithm with the filter gain correction for the case of measurement ...
Xiaogong Lin, Shusheng Xu, Yehai Xie
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Iterated square root cubature kalman filter with application to tightly coupled GNSS/INS
2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC), 2016An iterated filtering method is presented to improve the update stage of nonlinear filtering. First, we develop a generalized iterative framework for sigma point kalman filter by utilizing Gauss-Newton algorithm. A simplified iterated square root cubature kalman filter (SCKF) is proposed with application to tightly coupled GNSS/INS, where the linear ...
null Bingbo Cui +2 more
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An adaptive square root cubature Kalman filter based SLAM algorithm for mobile robots
2015 IEEE International Conference on Mechatronics and Automation (ICMA), 2015For simultaneous localization and mapping (SLAM) of mobile robots, an innovative solution is proposed, named adaptive square root cubature Kalman filter based SLAM algorithm (ASRCKF-SLAM). The main contribution of the proposed algorithm lies that: 1) Square root factors are used in the proposed ASRCKF-SLAM algorithm to improve the calculation ...
Jun Cai, Xiaolin Zhong
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Square-root cubature Kalman filter based power system dynamic state estimation
Sustainable Energy, Grids and Networks, 2022Vedik Basetti +2 more
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Levenberg-Marquardt Method Based Iteration Square Root Cubature Kalman Filter ant its Applications
2017 International Conference on Computer Network, Electronic and Automation (ICCNEA), 2017To improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation error and nonlinearity of measurement equation, we obtain Levenberg-Marquardt (abbr. L-M) method based iteration square root cubature Kalman filter (ISRCKFLM) combining the measurement update of square root cubature Kalman filter (SRCKF) with ...
Mu Jing, Wang Changyuan
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Square-Root Cubature Kalman Filters for Training Recurrent Type-2 Fuzzy Neural Networks
2019 27th Iranian Conference on Electrical Engineering (ICEE), 2019This paper proposes a novel learning algorithm benefitting from square-root cubature Kalman filters for training recurrent interval type-2 fuzzy neural networks. The recurrence property in this network is feeding the output of each input to itself. Simulations results show the effectiveness of the proposed network and the proposed learning algorithm.
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