Sampled-data filtering with error covariance assignment
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 ...
Biao Huang, Zidong Wang
exaly +2 more sources
A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective [PDF]
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
doaj +1 more source
Initialization of SINS/GNSS Error Covariance Matrix Based on Error States Correlation
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
doaj +1 more source
Collision Prediction of Spacecraft for Space Traffic Management [PDF]
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
doaj +1 more source
Scale-dependent background-error covariance localisation [PDF]
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
doaj +1 more source
Errors on errors – Estimating cosmological parameter covariance [PDF]
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
openaire +2 more sources
Some quantitative characteristics of error covariance for Kalman filters
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
doaj +1 more source
Cox Regression with Dependent Error in Covariates [PDF]
SummaryMany survival studies have error-contaminated covariates due to the lack of a gold standard of measurement. Furthermore, the error distribution can depend on the true covariates but the structure may be difficult to characterize; heteroscedasticity is a common manifestation.
Yijian Huang, Ching-Yun Wang
openaire +2 more sources
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation [PDF]
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
doaj +1 more source
Sparse Approximation of the Precision Matrices for the Wide-Swath Altimeters
The upcoming technology of wide-swath altimetry from space will deliver a large volume of data on the ocean surface at unprecedentedly high spatial resolution.
Max Yaremchuk
doaj +1 more source

