Package org.orekit.estimation.sequential
Class AbstractCovarianceMatrixProvider
- java.lang.Object
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- org.orekit.estimation.sequential.AbstractCovarianceMatrixProvider
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- All Implemented Interfaces:
CovarianceMatrixProvider
- Direct Known Subclasses:
ConstantProcessNoise
,UnivariateProcessNoise
public abstract class AbstractCovarianceMatrixProvider extends Object implements CovarianceMatrixProvider
Abstract provider handling a predefined initial covariance matrix.This class always provides a predefined initial noise matrix.
- Since:
- 9.2
- Author:
- Luc Maisonobe
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Constructor Summary
Constructors Modifier Constructor Description protected
AbstractCovarianceMatrixProvider(RealMatrix initialNoiseMatrix)
Simple constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description RealMatrix
getInitialCovarianceMatrix(SpacecraftState initial)
Get the initial covariance matrix.-
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.orekit.estimation.sequential.CovarianceMatrixProvider
getProcessNoiseMatrix
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Constructor Detail
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AbstractCovarianceMatrixProvider
protected AbstractCovarianceMatrixProvider(RealMatrix initialNoiseMatrix)
Simple constructor.- Parameters:
initialNoiseMatrix
- initial process noise
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Method Detail
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getInitialCovarianceMatrix
public RealMatrix getInitialCovarianceMatrix(SpacecraftState initial)
Get the initial covariance matrix.The initial covariance matrix is a covariance matrix corresponding to the parameters managed by the
Kalman estimator
. The number of rows/columns and their order are as follows:- The first 6 components correspond to the 6 orbital parameters of the associated propagator. All 6 parameters must always be present, regardless of the fact they are estimated or not.
- The following components correspond to the subset of propagation parameters of the associated propagator that are estimated.
- The remaining components correspond to the subset of measurements parameters that are estimated, considering all measurements, even the ones that correspond to spacecrafts not related to the associated propagator
In most cases, the initial covariance matrix will be the output matrix of a previous run of the Kalman filter.
- Specified by:
getInitialCovarianceMatrix
in interfaceCovarianceMatrixProvider
- Parameters:
initial
- initial state state- Returns:
- physical (i.e. non normalized) initial covariance matrix
- See Also:
PropagatorBuilder.getOrbitalParametersDrivers()
,PropagatorBuilder.getPropagationParametersDrivers()
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