Package org.orekit.estimation.sequential

The sequential package provides an implementation of a Kalman Filter engine to perform an orbit determination.

See: Description

Interface Summary

Interface	Description
CovarianceMatrixProvider	Provider for process noise matrices.
KalmanEstimation	Interface for accessing Kalman filter estimations.
KalmanObserver	Observer for Kalman filter estimations.

Class Summary

Class	Description
AbstractCovarianceMatrixProvider	Abstract provider handling a predefined initial covariance matrix.
AbstractKalmanModel	Abstract class defining the process model dynamics to use with a KalmanEstimator.
ConstantProcessNoise	Provider for constant process noise matrices.
DSSTKalmanModel	Class defining the process model dynamics to use with a KalmanEstimator.
KalmanEstimator	Implementation of a Kalman filter to perform orbit determination.
KalmanEstimatorBuilder	Builder for a Kalman filter estimator.
KalmanModel	Class defining the process model dynamics to use with a KalmanEstimator.
MeasurementDecorator	Decorator adding Measurement API to an ObservedMeasurement.
TLEKalmanModel	Class defining the process model dynamics to use with a KalmanEstimator.
UnivariateProcessNoise	Provider for a temporal evolution of the process noise matrix.

Package org.orekit.estimation.sequential Description

The sequential package provides an implementation of a Kalman Filter engine to perform an orbit determination.

Users will typically create one instance of this object, register all observation data as measurements with their included modifiers, and run the kalman filter. For each processed measurement, a fully configured propagator will be available, as well as all estimated parameters individually.