Measurement Noise Recommendation for Efficient Kalman Filtering over a Large Amount of Sensor Data
Sensors, 2019 To effectively maintain and analyze a large amount of real-time sensor data, one often uses a filtering technique that reflects characteristics of original data well.
Sebin Park +3 more
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Sensors, 2008 This paper proposes a new distributed Kalman filtering fusion with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering.
Donghua Wang +5 more
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Advancements in Buoy Wave Data Processing through the Application of the Sage–Husa Adaptive Kalman Filtering Algorithm [PDF]
Sensors, 2023 In this paper, we propose a combined filtering method rooted in the application of the Sage–Husa Adaptive Kalman filtering, designed specifically to process wave sensor data.
Sha Jiang, Yonghua Chen, Qingkui Liu
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Kalman filtering to reduce measurement noise of sample entropy: An electroencephalographic study. [PDF]
PLoS ONEIn the analysis of electroencephalography (EEG), entropy can be used to quantify the rate of generation of new information. Entropy has long been known to suffer from variance that arises from its calculation.
Nan Zhang +6 more
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Journal of Statistical Software, 2011 Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman ...
Fernando Tusell
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The Optimal Distributed Kalman Filtering Fusion With Linear Equality Constraint
IEEE Access, 2021 In this paper, the optimal distributed Kalman filtering fusion with linear equality constraint (LEC) is proposed. When the Kalman filter subject to LEC is applied in state estimation of distributed linear dynamic system, all local error covariance ...
Hua Li, Shengli Zhao
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Two-Stage Cubature Kalman Filtering Based on T-Transform and Its Application
Complexity, 2021 According to the actual application system model which has bias, this paper analyzes the shortage of the conventional augmented algorithm, the two-stage cubature Kalman filtering algorithm, which is presented on the basis of a two-stage nonlinear ...
Lu Zhang +3 more
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Inverse problem of incomplete boundaries and unknown parameters in two-dimensional Poisson equation
Nantong Daxue xuebao. Ziran kexue ban, 2022 The inverse problem of Poisson equation with incomplete boundary or unknown parameters have been solved by using the method of fundamental solutions (MFS) and Kalman filtering technique.
WANG Yue; JIANG Quan
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Double hybrid Kalman filtering for state estimation of dynamical systems [PDF]
ITM Web of Conferences, 2019 In this paper authors present a new approaches to the hybrid Kalman filtering and modified hybrid Kalman filtering, with the changed order of methods inside (Unscented Kalman Filter and Extended Kalman Filter).
Michalski Jacek +2 more
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A GENERIC PROBABILISTIC MODEL AND A HIERARCHICAL SOLUTION FOR SENSOR LOCALIZATION IN NOISY AND RESTRICTED CONDITIONS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 A generic probabilistic model, under fundamental Bayes’ rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors.
S. Ji, S. Ji, X. Yuan
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