SemiAnalyticalKalmanEstimatorBuilder.java

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package org.orekit.estimation.sequential;

import org.hipparchus.linear.MatrixDecomposer;
import org.hipparchus.linear.QRDecomposer;
import org.orekit.errors.OrekitException;
import org.orekit.errors.OrekitMessages;
import org.orekit.propagation.conversion.DSSTPropagatorBuilder;
import org.orekit.utils.ParameterDriversList;

/** Builder for a Semi-analytical Kalman Filter.
 * @author Julie Bayard
 * @author Bryan Cazabonne
 * @author Maxime Journot
 * @since 11.1
 */
public class SemiAnalyticalKalmanEstimatorBuilder {

    /** Decomposer to use for the correction phase. */
    private MatrixDecomposer decomposer;

    /** Builder for propagator. */
    private DSSTPropagatorBuilder dsstPropagatorBuilder;

    /** Process noise matrix provider. */
    private CovarianceMatrixProvider processNoiseMatrixProvider;

    /** Estimated measurements parameters. */
    private ParameterDriversList estimatedMeasurementsParameters;

    /** Process noise matrix provider for measurement parameters. */
    private CovarianceMatrixProvider measurementProcessNoiseMatrix;

    /** Default constructor.
     *  Set an Extended Semi-analytical Kalman Filter.
     */
    public SemiAnalyticalKalmanEstimatorBuilder() {
        this.decomposer                      = new QRDecomposer(1.0e-15);
        this.dsstPropagatorBuilder           = null;
        this.processNoiseMatrixProvider      = null;
        this.estimatedMeasurementsParameters = new ParameterDriversList();
        this.measurementProcessNoiseMatrix   = null;
    }

    /** Construct a {@link KalmanEstimator} from the data in this builder.
     * <p>
     * Before this method is called, {@link #addPropagationConfiguration(DSSTPropagatorBuilder,
     * CovarianceMatrixProvider) addPropagationConfiguration()} must have been called
     * at least once, otherwise configuration is incomplete and an exception will be raised.
     * </p>
     * @return a new {@link KalmanEstimator}.
     */
    public SemiAnalyticalKalmanEstimator build() {
        if (dsstPropagatorBuilder == null) {
            throw new OrekitException(OrekitMessages.NO_PROPAGATOR_CONFIGURED);
        }
        return new SemiAnalyticalKalmanEstimator(decomposer, dsstPropagatorBuilder, processNoiseMatrixProvider,
                                                 estimatedMeasurementsParameters, measurementProcessNoiseMatrix);
    }

    /** Configure the matrix decomposer.
     * @param matrixDecomposer decomposer to use for the correction phase
     * @return this object.
     */
    public SemiAnalyticalKalmanEstimatorBuilder decomposer(final MatrixDecomposer matrixDecomposer) {
        decomposer = matrixDecomposer;
        return this;
    }

    /** Add a propagation configuration.
     * <p>
     * This method must be called once initialize the propagator builder
     * used by the Kalman Filter.
     * </p>
     * @param builder The propagator builder to use in the Kalman filter.
     * @param provider The process noise matrices provider to use, consistent with the builder.
     * @return this object.
     */
    public SemiAnalyticalKalmanEstimatorBuilder addPropagationConfiguration(final DSSTPropagatorBuilder builder,
                                                                            final CovarianceMatrixProvider provider) {
        dsstPropagatorBuilder      = builder;
        processNoiseMatrixProvider = provider;
        return this;
    }

    /** Configure the estimated measurement parameters.
     * <p>
     * If this method is not called, no measurement parameters will be estimated.
     * </p>
     * @param estimatedMeasurementsParams The estimated measurements' parameters list.
     * @param provider covariance matrix provider for the estimated measurement parameters
     * @return this object.
     */
    public SemiAnalyticalKalmanEstimatorBuilder estimatedMeasurementsParameters(final ParameterDriversList estimatedMeasurementsParams,
                                                                                final CovarianceMatrixProvider provider) {
        estimatedMeasurementsParameters = estimatedMeasurementsParams;
        measurementProcessNoiseMatrix   = provider;
        return this;
    }

}