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Distributed finite time cubature information filtering with unknown correlated measurement noises
ISA Transactions, 2021This paper addresses the distributed state estimation problem for a class of discrete nonlinear system over sensor networks subject to unknown correlated measurement noises. Firstly, under the condition of network connectivity, a novel communication protocol is developed to ensure every sensor node can gather the information distributed throughout the ...
Yuan, Liang +5 more
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Double-Layer Cubature Kalman Filter for Nonlinear Estimation
Sensors, 2019 The cubature Kalman filter (CKF) has poor performance in strongly nonlinear systems while the cubature particle filter has high computational complexity induced by stochastic sampling.
Feng Yang
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Two-stage High-degree Cubature Information Filter
Journal of Intelligent & Fuzzy Systems, 2017In the system with unknown random bias, it is common to treat the bias as part of the system state, that is augmented state Kalman filter (ASKF) which will lead to overflow and can not work in computer system. To avoid use the ASKF, two-stage Kalman filter was proposed. It is generally known that the computational complexity of Kalman Filter is highly
Lu Zhang +3 more
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Attitude Estimation Based on Robust Information Cubature Quaternion Filter
Circuits, Systems, and Signal Processing, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiaohang Wu, Kemao Ma
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Improved square-root cubature information filter
Transactions of the Institute of Measurement and Control, 2016In this paper, a theoretical comparison between existing the sigma-point information filter (SPIF) framework and the unscented information filter (UIF) framework is presented. It is shown that the SPIF framework is identical to the sigma-point Kalman filter (SPKF).
Yulong Huang +3 more
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Cubature information filters with correlated noises and their applications in decentralized fusion
Signal Processing, 2014Data fusion for nonlinear systems is one of the challenging topics in state estimation and target tracking recently. We study decentralized cubature Kalman fusion in this paper. Cubature Kalman filter (CKF) is a more effective method than the conventional nonlinear filters, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF).
Quanbo Ge, Daxing Xu, Chenglin Wen
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Distributed cubature information filtering based on weighted average consensus
Neurocomputing, 2017In this paper, the distributed state estimation (DSE) problem for a class of discrete-time nonlinear systems over sensor networks is investigated. First, based on weighted average consensus, a new DSE algorithm named distributed cubature information filtering (DCIF) algorithm is developed to address the high-dimensional nonlinear DSE problem.
Qian Chen 0017 +4 more
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Finite Time Decentralized Cubature Information Filtering with Directed Graph
2020 Chinese Automation Congress (CAC), 2020This paper focuses on the distributed state estimation problem with finite communication time and directed graph for the nonlinear discrete system. A finite time decentralized cubature information filtering algorithm is proposed, of which the goal is to estimate the interested states in a fully distributed manner.
Yuan Liang +5 more
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Multi-sensor Information Fusion Cubature Kalman Particle Filter
2016 9th International Symposium on Computational Intelligence and Design (ISCID), 2016Distributed parameter estimation is more practical in wireless sensor networks, as it has less communication overhead and is robust in large scale sensor networks. To solve the state estimation problem of nonlinear and non-Gaussian system, we propose a distributed cubature Kalman particle filter, which use cubature Kalman filter to generate the ...
Jinwang Huang +2 more
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Consensus-based cubature information filtering for sensor networks with incomplete measurements
Neurocomputing, 2019Abstract Consensus-based distributed filtering is an effective technique for state estimation or data fusion over sensor networks. However, nonlinearity of systems as well as network-induced incomplete information problems are the main obstacles on the way.
Ji Liu, Qing Shao, Chenchao Hua
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