Package org.orekit.estimation.sequential

Interface CovarianceMatrixProvider

All Known Implementing Classes:

AbstractCovarianceMatrixProvider, ConstantProcessNoise, UnivariateProcessNoise

public interface CovarianceMatrixProvider

Provider for process noise matrices.

Since:

9.2

Author:

Luc Maisonobe

Method Summary

Modifier and Type	Method	Description
org.hipparchus.linear.RealMatrix	getInitialCovarianceMatrix(SpacecraftState initial)	Get the initial covariance matrix.
org.hipparchus.linear.RealMatrix	getProcessNoiseMatrix(SpacecraftState previous, SpacecraftState current)	Get the process noise matrix between previous and current states.

Method Detail

getInitialCovarianceMatrix

org.hipparchus.linear.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.

Parameters:

initial - initial state state

Returns:

physical (i.e. non normalized) initial covariance matrix

See Also:

PropagatorBuilder.getOrbitalParametersDrivers(), PropagatorBuilder.getPropagationParametersDrivers()

getProcessNoiseMatrix

org.hipparchus.linear.RealMatrix getProcessNoiseMatrix(SpacecraftState previous,
                                                       SpacecraftState current)

Get the process noise matrix between previous and current states.

The process noise 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 process noise for the part corresponding to measurements (the final rows and columns) will be set to 0 for the process noise corresponding to the evolution between a non-null previous and current state.

Parameters:

previous - previous state

current - current state

Returns:

physical (i.e. non normalized) process noise matrix between previous and current states

See Also:

PropagatorBuilder.getOrbitalParametersDrivers(), PropagatorBuilder.getPropagationParametersDrivers()