Sequential Covariance Intersection Fusion Robust Time-Varying Kalman Filters with Uncertainties of Noise Variances for Advanced Manufacturing [PDF]
Micromachines, 2022 This paper addresses the robust Kalman filtering problem for multisensor time-varying systems with uncertainties of noise variances. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper ...
Wenjuan Qi, Shigang Wang
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A Review of Dynamic Phasor Estimation by Non-Linear Kalman Filters
IEEE Access, 2022 Phasor estimation under dynamic conditions has been under study recently by relaxing the amplitude and phase of the static phasor. This paper will review some methods to estimate dynamic phasor by nonlinear Kalman filters.
Jalal Khodaparast
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Possibilities of Using Kalman Filters in Indoor Localization
Mathematics, 2020 Kalman filters are a set of algorithms based on the idea of a filter described by Rudolf Emil Kalman in 1960. Kalman filters are used in various application domains, including localization, object tracking, and navigation.
Katerina Fronckova, Pavel Prazak
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KalmanFormer: using transformer to model the Kalman Gain in Kalman Filters [PDF]
Frontiers in NeuroroboticsIntroductionTracking the hidden states of dynamic systems is a fundamental task in signal processing. Recursive Kalman Filters (KF) are widely regarded as an efficient solution for linear and Gaussian systems, offering low computational complexity ...
Siyuan Shen +4 more
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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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Controlling balance in an ensemble Kalman filter [PDF]
Nonlinear Processes in Geophysics, 2014 We present a method to control unbalanced fast dynamics in an ensemble Kalman filter by introducing a weak constraint on the imbalance in a spatially sparse observational network.
G. A. Gottwald
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Applications of Kalman and Extended Kalman Filtering to Target Tracking [PDF]
المجلة العراقية للعلوم الاحصائية, 2006 This study deals with the famous trackers named Kalman and extended Kalman filters. This is introduced by describing the state space representation approach to model the target system.
Basil Y. Thanoon +2 more
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Machines, 2023 This paper analyzes the performance of Kalman filter-based estimators for robust filtering and rotor asymmetry detection in wound rotor induction machines (WRIMs) using real-time data. Filter models were designed based on an extended model of WRIMs.
Furzana John Basha, Kumar Somasundaram
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Comparative study of state and unknown input estimation for continuous–discrete stochastic systems
Franklin Open, 2022 Joint state and unknown input estimation for continuous–discrete stochastic systems can be classified into two types: with and without modeling of unknown inputs.
Peng Lu
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A New Fusion Estimation Method for Multi-Rate Multi-Sensor Systems With Missing Measurements
IEEE Access, 2020 A new fusion strategy is introduced in this article to estimate state for multi-rate multi-sensor systems with missing measurements. N sensors, which possess various sampling rates, render the measurements. Missing measurements with a certain probability
Mojtaba Kordestani +3 more
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