Results 1 to 10 of about 147,262 (309)
Sampled-data filtering with error covariance assignment
IEEE Transactions on Signal Processing, 2001 We consider the sampled-data filtering problem by proposing a new performance criterion in terms of the estimation error covariance. An innovation approach to sampled-data filtering is presented. First, the definition of the estimation covariance e for a sampled-data system is given, then the sampled-data filtering problem is reduced to the Kalman ...
Zidong Wang, Biao Huang
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Measurement Error Models with Nonconstant Covariance Matrices
Journal of Multivariate Analysis, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Reinaldo B Arellano-Valle +1 more
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A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective [PDF]
Nonlinear Processes in Geophysics, 2021 This contribution addresses the characterization of the model-error covariance matrix from the new theoretical perspective provided by the parametric Kalman filter method which approximates the covariance dynamics from the parametric evolution of a ...
O. Pannekoucke +6 more
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Collision Prediction of Spacecraft for Space Traffic Management [PDF]
فصلنامه علوم و فناوری فضایی, 2022 In this article collision probability method is used to satellite collision risk analysis. Among different methods introduced for determining collision probability, Patera's (2005) and Chan methods are chosen to define Noor satellite collision to the ...
Hamid Kazemi, Samaneh Elahian
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Initialization of SINS/GNSS Error Covariance Matrix Based on Error States Correlation
IEEE Access, 2023 The traditional Strapdown Inertial Navigation System (SINS)/Global Navigation Satellite System (GNSS) integrated system uses standard Kalman Filter (KF) to estimate the error states, which weakens the correlation between the different error components to
Jun Tang +3 more
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Scale-dependent background-error covariance localisation [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2015 A new approach is presented and evaluated for efficiently applying scale-dependent spatial localisation to ensemble background-error covariances within an ensemble-variational data assimilation system.
Mark Buehner, Anna Shlyaeva
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Some quantitative characteristics of error covariance for Kalman filters
Tellus: Series A, Dynamic Meteorology and Oceanography, 2021 Some quantitative characteristics of error covariance are studied for linear Kalman filters. These quantitative characteristics include the peak value and location in the matrix, the decay rate from peak to bottom, and some algebraic constraints of the ...
Wei Kang, Liang Xu
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Errors on errors – Estimating cosmological parameter covariance [PDF]
Proceedings of the International Astronomical Union, 2014 AbstractCurrent and forthcoming cosmological data analyses share the challenge of huge datasets alongside increasingly tight requirements on the precision and accuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central values of parameters but, equally important, also
Joachimi, Benjamin, Taylor, Andy
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pyGNMF: A Python library for implementation of generalised non-negative matrix factorisation method
SoftwareX, 2022 This article introduces a Python library named pyGNMF, which implements the recently proposed generalised non-negative matrix factorisation (GNMF) method.
Nirav L. Lekinwala, Mani Bhushan
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Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation [PDF]
Geoscientific Model Development, 2015 In this study, we examined the structure of an ensemble-based coupled atmosphere–chemistry forecast error covariance. The Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF-Chem), a coupled atmosphere–chemistry model, was used to ...
S. K. Park, S. Lim, M. Zupanski
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