Position.java
- /* Copyright 2002-2025 CS GROUP
- * Licensed to CS GROUP (CS) under one or more
- * contributor license agreements. See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * CS licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
- package org.orekit.estimation.measurements;
- import java.util.Collections;
- import org.hipparchus.exception.LocalizedCoreFormats;
- import org.hipparchus.geometry.euclidean.threed.Vector3D;
- import org.hipparchus.util.FastMath;
- import org.orekit.errors.OrekitException;
- import org.orekit.propagation.SpacecraftState;
- import org.orekit.time.AbsoluteDate;
- import org.orekit.utils.TimeStampedPVCoordinates;
- /** Class modeling a position only measurement.
- * <p>
- * For position-velocity measurement see {@link PV}.
- * </p>
- * @see PV
- * @author Luc Maisonobe
- * @since 9.3
- */
- public class Position extends AbstractMeasurement<Position> {
- /** Type of the measurement. */
- public static final String MEASUREMENT_TYPE = "Position";
- /** Identity matrix, for states derivatives. */
- private static final double[][] IDENTITY = new double[][] {
- {
- 1, 0, 0, 0, 0, 0
- }, {
- 0, 1, 0, 0, 0, 0
- }, {
- 0, 0, 1, 0, 0, 0
- }
- };
- /** Covariance matrix of the position only measurement (size 3x3). */
- private final double[][] covarianceMatrix;
- /** Constructor with one double for the standard deviation.
- * <p>The double is the position's standard deviation, common to the 3 position's components.</p>
- * <p>
- * The measurement must be in the orbit propagation frame.
- * </p>
- * @param date date of the measurement
- * @param position position
- * @param sigmaPosition theoretical standard deviation on position components
- * @param baseWeight base weight
- * @param satellite satellite related to this measurement
- * @since 9.3
- */
- public Position(final AbsoluteDate date, final Vector3D position,
- final double sigmaPosition, final double baseWeight,
- final ObservableSatellite satellite) {
- this(date, position,
- new double[] {
- sigmaPosition,
- sigmaPosition,
- sigmaPosition
- }, baseWeight, satellite);
- }
- /** Constructor with one vector for the standard deviation.
- * <p>The 3-sized vector represents the square root of the diagonal elements of the covariance matrix.</p>
- * <p>The measurement must be in the orbit propagation frame.</p>
- * @param date date of the measurement
- * @param position position
- * @param sigmaPosition 3-sized vector of the standard deviations of the position
- * @param baseWeight base weight
- * @param satellite satellite related to this measurement
- * @since 9.3
- */
- public Position(final AbsoluteDate date, final Vector3D position,
- final double[] sigmaPosition, final double baseWeight, final ObservableSatellite satellite) {
- this(date, position, buildPvCovarianceMatrix(sigmaPosition), baseWeight, satellite);
- }
- /** Constructor with full covariance matrix and all inputs.
- * <p>The fact that the covariance matrix is symmetric and positive definite is not checked.</p>
- * <p>The measurement must be in the orbit propagation frame.</p>
- * @param date date of the measurement
- * @param position position
- * @param covarianceMatrix 3x3 covariance matrix of the position only measurement
- * @param baseWeight base weight
- * @param satellite satellite related to this measurement
- * @since 9.3
- */
- public Position(final AbsoluteDate date, final Vector3D position,
- final double[][] covarianceMatrix, final double baseWeight,
- final ObservableSatellite satellite) {
- super(date,
- new double[] {
- position.getX(), position.getY(), position.getZ()
- }, extractSigmas(covarianceMatrix),
- new double[] {
- baseWeight, baseWeight, baseWeight
- }, Collections.singletonList(satellite));
- this.covarianceMatrix = covarianceMatrix.clone();
- }
- /** Get the position.
- * @return position
- */
- public Vector3D getPosition() {
- final double[] pv = getObservedValue();
- return new Vector3D(pv[0], pv[1], pv[2]);
- }
- /** Get the covariance matrix.
- * @return the covariance matrix
- */
- public double[][] getCovarianceMatrix() {
- return covarianceMatrix.clone();
- }
- /** Get the correlation coefficients matrix.
- * <p>This is the 3x3 matrix M such that:
- * <p>Mij = Pij/(σi.σj)
- * <p>Where:
- * <ul>
- * <li>P is the covariance matrix
- * <li>σi is the i-th standard deviation (σi² = Pii)
- * </ul>
- * @return the correlation coefficient matrix (3x3)
- */
- public double[][] getCorrelationCoefficientsMatrix() {
- // Get the standard deviations
- final double[] sigmas = getTheoreticalStandardDeviation();
- // Initialize the correlation coefficients matric to the covariance matrix
- final double[][] corrCoefMatrix = new double[sigmas.length][sigmas.length];
- // Divide by the standard deviations
- for (int i = 0; i < sigmas.length; i++) {
- for (int j = 0; j < sigmas.length; j++) {
- corrCoefMatrix[i][j] = covarianceMatrix[i][j] / (sigmas[i] * sigmas[j]);
- }
- }
- return corrCoefMatrix;
- }
- /** {@inheritDoc} */
- @Override
- protected EstimatedMeasurementBase<Position> theoreticalEvaluationWithoutDerivatives(final int iteration, final int evaluation,
- final SpacecraftState[] states) {
- // PV value
- final TimeStampedPVCoordinates pv = states[0].getPVCoordinates();
- // prepare the evaluation
- final EstimatedMeasurementBase<Position> estimated =
- new EstimatedMeasurementBase<>(this, iteration, evaluation, states,
- new TimeStampedPVCoordinates[] {
- pv
- });
- estimated.setEstimatedValue(pv.getPosition().getX(), pv.getPosition().getY(), pv.getPosition().getZ());
- return estimated;
- }
- /** {@inheritDoc} */
- @Override
- protected EstimatedMeasurement<Position> theoreticalEvaluation(final int iteration, final int evaluation,
- final SpacecraftState[] states) {
- final EstimatedMeasurement<Position> estimated = new EstimatedMeasurement<>(theoreticalEvaluationWithoutDerivatives(iteration, evaluation, states));
- // partial derivatives with respect to state
- estimated.setStateDerivatives(0, IDENTITY);
- return estimated;
- }
- /** Extract standard deviations from a 3x3 position covariance matrix.
- * Check the size of the position covariance matrix first.
- * @param pCovarianceMatrix the 3x" position covariance matrix
- * @return the standard deviations (3-sized vector), they are
- * the square roots of the diagonal elements of the covariance matrix in input.
- */
- private static double[] extractSigmas(final double[][] pCovarianceMatrix) {
- // Check the size of the covariance matrix, should be 3x3
- if (pCovarianceMatrix.length != 3 || pCovarianceMatrix[0].length != 3) {
- throw new OrekitException(LocalizedCoreFormats.DIMENSIONS_MISMATCH_2x2,
- pCovarianceMatrix.length, pCovarianceMatrix[0],
- 3, 3);
- }
- // Extract the standard deviations (square roots of the diagonal elements)
- final double[] sigmas = new double[3];
- for (int i = 0; i < sigmas.length; i++) {
- sigmas[i] = FastMath.sqrt(pCovarianceMatrix[i][i]);
- }
- return sigmas;
- }
- /** Build a 3x3 position covariance matrix from a 3-sized vector (position standard deviations).
- * Check the size of the vector first.
- * @param sigmaP 3-sized vector with position standard deviations
- * @return the 3x3 position covariance matrix
- */
- private static double[][] buildPvCovarianceMatrix(final double[] sigmaP) {
- // Check the size of the vector first
- if (sigmaP.length != 3) {
- throw new OrekitException(LocalizedCoreFormats.DIMENSIONS_MISMATCH, sigmaP.length, 3);
- }
- // Build the 3x3 position covariance matrix
- final double[][] pvCovarianceMatrix = new double[3][3];
- for (int i = 0; i < sigmaP.length; i++) {
- pvCovarianceMatrix[i][i] = sigmaP[i] * sigmaP[i];
- }
- return pvCovarianceMatrix;
- }
- }