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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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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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Spectral diagonal ensemble Kalman filters [PDF]
Nonlinear Processes in Geophysics, 2015 A new type of ensemble Kalman filter is developed, which is based on replacing the sample covariance in the analysis step by its diagonal in a spectral basis.
I. Kasanický, J. Mandel, M. Vejmelka
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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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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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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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Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
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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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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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Autodifferentiable Ensemble Kalman Filters
SIAM Journal on Mathematics of Data Science, 2022 Data assimilation is concerned with sequentially estimating a temporally-evolving state. This task, which arises in a wide range of scientific and engineering applications, is particularly challenging when the state is high-dimensional and the state-space dynamics are unknown.
Yuming Chen +2 more
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