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   Articles with "error covariance" as a keyword



A conjugate BFGS method for accurate estimation of a posterior error covariance matrix in a linear inverse problem

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recommendations! Published in 2020 at "Quarterly Journal of the Royal Meteorological Society"

DOI: 10.1002/qj.3838

Abstract: One effective data assimilation/inversion method is the four‐dimensional variational method (4D‐Var). However, it is a non‐trivial task for a conventional 4D‐Var to estimate a posterior error covariance matrix. This study proposes a method to estimate… read more here.

Keywords: matrix; error covariance; method; posterior error ... See more keywords

Sampling and misspecification errors in the estimation of observation‐error covariance matrices using observation‐minus‐background and observation‐minus‐analysis statistics

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recommendations! Published in 2024 at "Quarterly Journal of the Royal Meteorological Society"

DOI: 10.1002/qj.4750

Abstract: Specification of the observation‐error covariance matrix for data assimilation systems affects the observation information content retained by the analysis, particularly for observations known to have correlated observation errors (e.g., geostationary satellite and Doppler radar data).… read more here.

Keywords: observation minus; error covariance; observation error; observation ... See more keywords

Model and observation‐error covariance matrix information in the physical nudging equations

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recommendations! Published in 2025 at "Quarterly Journal of the Royal Meteorological Society"

DOI: 10.1002/qj.4979

Abstract: In this work we show how to extend the deterministic physical nudging scheme in order to include two important ingredients, the model and observation‐error covariance matrices, which are common features of classical data‐assimilation schemes. The… read more here.

Keywords: observation error; error covariance; model observation; physical nudging ... See more keywords

Boundedness of the Kalman Filter Revisited

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recommendations! Published in 2021 at "IFAC-PapersOnLine"

DOI: 10.1016/j.ifacol.2021.08.381

Abstract: Abstract The boundedness of the Kalman filter, as the first cornerstone of its stability analysis, has been proved in the classical literature through upper bounds of non-recursive filters in the sense of the trace of… read more here.

Keywords: filter; kalman filter; boundedness kalman; error covariance ... See more keywords

Analysis of geometric selection of the data-error covariance inflation for ES-MDA

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recommendations! Published in 2019 at "Journal of Petroleum Science and Engineering"

DOI: 10.1016/j.petrol.2019.06.032

Abstract: Abstract The ensemble smoother with multiple data assimilation (ES-MDA) has become a popular assisted history-matching method. In its standard form, the method requires the specification of the number of iterations in advance. If the selected… read more here.

Keywords: selection data; error covariance; data error; inflation ... See more keywords

Improving Convective Precipitation Forecasts Using Ensemble‐Based Background Error Covariance in 3DVAR Radar Assimilation System

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recommendations! Published in 2020 at "Earth and Space Science"

DOI: 10.1029/2019ea000667

Abstract: Skillful quantitative precipitation forecast using the numerical weather prediction model relies on an accurate estimate of the atmospheric state as an initial condition. Variational assimilation methods (VAR) have the potential to provide improved initial state… read more here.

Keywords: assimilation; background error; model; error ... See more keywords

Characterization of the Ionospheric Vertical Error Correlation Lengths Based on Global Ionosonde Observations

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recommendations! Published in 2024 at "Space Weather"

DOI: 10.1029/2023sw003743

Abstract: Data assimilation is one of the most important approaches to monitoring the variations of ionospheric electron densities. The construction of the background error covariance matrix is an important component of ionospheric data assimilations. To construct… read more here.

Keywords: vertical error; correlation; ionospheric vertical; error covariance ... See more keywords

Cholesky-KalmanNet: Model-Based Deep Learning With Positive Definite Error Covariance Structure

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recommendations! Published in 2025 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2024.3519265

Abstract: State estimation from noisy observations is crucial across various fields. Traditional methods such as Kalman, Extended Kalman, and Unscented Kalman Filter often struggle with nonlinearities, model inaccuracies, and high observation noise. This letter introduces Cholesky-KalmanNet… read more here.

Keywords: error covariance; cholesky kalmannet; model; estimation ... See more keywords

Performance Analysis of Distributed Filtering Under Misspecified Noise Covariances

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recommendations! Published in 2025 at "IEEE Transactions on Automatic Control"

DOI: 10.1109/tac.2025.3565956

Abstract: This article systematically investigates the performance of the consensus-based distributed filter under misspecified noise covariances. First, we introduce four quantities: the nominal filter parameter, the nominal estimation error covariance, the ideal filter parameter, and the… read more here.

Keywords: misspecified noise; estimation error; error covariance; covariance ... See more keywords

Distributed Kalman Filter With Faulty/Reliable Sensors Based on Wasserstein Average Consensus

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recommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"

DOI: 10.1109/tcsii.2022.3146418

Abstract: This brief considers distributed Kalman filtering problem for systems with sensor faults. A trust-based classification fusion strategy is proposed to resist against sensor faults. First, the local sensors collect measurements and then update their state… read more here.

Keywords: distributed kalman; wasserstein average; filter faulty; kalman filter ... See more keywords

Compensation Filtering for Spacecraft Attitude Estimation Using Error-Covariance Reconstruction

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recommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2022.3160555

Abstract: Traditional spacecraft attitude estimation algorithms normally require the assumption that the true quaternion approximates to the estimated value. Otherwise, it may lead to a large truncation error. However, this assumption is difficult to be always… read more here.

Keywords: error covariance; spacecraft attitude; error; estimation ... See more keywords