Package org.orekit.estimation.sequential

Class KalmanEstimatorBuilder

java.lang.Object
org.orekit.estimation.sequential.KalmanEstimatorBuilder
public class KalmanEstimatorBuilder extends Object
Builder for a Kalman filter estimator.
Since:
9.2
Author:
Romain Gerbaud, Maxime Journot

  • Constructor Details

    • KalmanEstimatorBuilder

      public KalmanEstimatorBuilder()
      Default constructor. Set an extended Kalman filter, with linearized covariance prediction.

  • Method Details

    • build

      public KalmanEstimator build()
      Construct a KalmanEstimator from the data in this builder.

      Before this method is called, addPropagationConfiguration() must have been called at least once, otherwise configuration is incomplete and an exception will be raised.

      Returns:
      a new KalmanEstimator.

    • decomposer

      public KalmanEstimatorBuilder decomposer(MatrixDecomposer matrixDecomposer)
      Configure the matrix decomposer.
      Parameters:
      matrixDecomposer - decomposer to use for the correction phase
      Returns:
      this object.

    • addPropagationConfiguration

      public KalmanEstimatorBuilder addPropagationConfiguration(PropagatorBuilder builder, CovarianceMatrixProvider provider)
      Add a propagation configuration.

      This method must be called once for each propagator to managed with the Kalman estimator. The propagators order in the Kalman filter will be the call order.

      The provider should return a matrix with dimensions and ordering consistent with the builder configuration. The first 6 rows/columns correspond to the 6 orbital parameters. The remaining elements correspond to the subset of propagation parameters that are estimated, in the same order as propagatorBuilder.getPropagationParametersDrivers().getDrivers() (but filtering out the non selected drivers).

      Parameters:
      builder - The propagator builder to use in the Kalman filter.
      provider - The process noise matrices provider to use, consistent with the builder. This parameter can be equal to null if the input builder is an EphemerisPropagatorBuilder. Indeed, for ephemeris based estimation only measurement parameters are estimated. Therefore, the covariance related to dynamical parameters can be null.
      Returns:
      this object.
      See Also:

    • estimatedMeasurementsParameters

      public KalmanEstimatorBuilder estimatedMeasurementsParameters(ParameterDriversList estimatedMeasurementsParams, CovarianceMatrixProvider provider)
      Configure the estimated measurement parameters.

      If this method is not called, no measurement parameters will be estimated.

      Parameters:
      estimatedMeasurementsParams - The estimated measurements' parameters list.
      provider - covariance matrix provider for the estimated measurement parameters
      Returns:
      this object.
      Since:
      10.3