Examples with RangeRateMeasurementCreator org.orekit.estimation.measurements.RangeRateMeasurementCreator used on opensource projects

Example 1 with RangeRateMeasurementCreator

use of org.orekit.estimation.measurements.RangeRateMeasurementCreator in project Orekit by CS-SI.

the class IonoModifierTest method testRangeRateIonoModifier.

@Test
public void testRangeRateIonoModifier() throws OrekitException {
    Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
    final NumericalPropagatorBuilder propagatorBuilder = context.createBuilder(OrbitType.KEPLERIAN, PositionAngle.TRUE, true, 1.0e-6, 60.0, 0.001);
    // create perfect range measurements
    for (final GroundStation station : context.stations) {
        station.getEastOffsetDriver().setSelected(true);
        station.getNorthOffsetDriver().setSelected(true);
        station.getZenithOffsetDriver().setSelected(true);
    }
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurements = EstimationTestUtils.createMeasurements(propagator, new RangeRateMeasurementCreator(context, false), 1.0, 3.0, 300.0);
    propagator.setSlaveMode();
    final RangeRateIonosphericDelayModifier modifier = new RangeRateIonosphericDelayModifier(model, true);
    for (final ObservedMeasurement<?> measurement : measurements) {
        final AbsoluteDate date = measurement.getDate();
        final SpacecraftState refstate = propagator.propagate(date);
        RangeRate rangeRate = (RangeRate) measurement;
        EstimatedMeasurement<RangeRate> evalNoMod = rangeRate.estimate(0, 0, new SpacecraftState[] { refstate });
        // add modifier
        rangeRate.addModifier(modifier);
        // 
        EstimatedMeasurement<RangeRate> eval = rangeRate.estimate(0, 0, new SpacecraftState[] { refstate });
        final double diffMetersSec = eval.getEstimatedValue()[0] - evalNoMod.getEstimatedValue()[0];
        // TODO: check threshold
        Assert.assertEquals(0.0, diffMetersSec, 0.016);
    }
}

Example 2 with RangeRateMeasurementCreator

use of org.orekit.estimation.measurements.RangeRateMeasurementCreator in project Orekit by CS-SI.

the class BatchLSEstimatorTest method testKeplerRangeRate.

/**
 * Perfect range rate measurements with a perfect start
 * @throws OrekitException
 */
@Test
public void testKeplerRangeRate() throws OrekitException {
    Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
    final NumericalPropagatorBuilder propagatorBuilder = context.createBuilder(OrbitType.KEPLERIAN, PositionAngle.TRUE, true, 1.0e-6, 60.0, 1.0);
    // create perfect range rate measurements
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurements1 = EstimationTestUtils.createMeasurements(propagator, new RangeRateMeasurementCreator(context, false), 1.0, 3.0, 300.0);
    final List<ObservedMeasurement<?>> measurements = new ArrayList<ObservedMeasurement<?>>();
    measurements.addAll(measurements1);
    // create orbit estimator
    final BatchLSEstimator estimator = new BatchLSEstimator(new LevenbergMarquardtOptimizer(), propagatorBuilder);
    for (final ObservedMeasurement<?> rangerate : measurements) {
        estimator.addMeasurement(rangerate);
    }
    estimator.setParametersConvergenceThreshold(1.0e-3);
    estimator.setMaxIterations(10);
    estimator.setMaxEvaluations(20);
    EstimationTestUtils.checkFit(context, estimator, 2, 3, 0.0, 1.6e-2, 0.0, 3.4e-2, // we only have range rate...
    0.0, // we only have range rate...
    170.0, 0.0, 6.5e-2);
}

Example 3 with RangeRateMeasurementCreator

use of org.orekit.estimation.measurements.RangeRateMeasurementCreator in project Orekit by CS-SI.

the class BatchLSEstimatorTest method testKeplerRangeAndRangeRate.

/**
 * Perfect range and range rate measurements with a perfect start
 * @throws OrekitException
 */
@Test
public void testKeplerRangeAndRangeRate() throws OrekitException {
    Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
    final NumericalPropagatorBuilder propagatorBuilder = context.createBuilder(OrbitType.KEPLERIAN, PositionAngle.TRUE, true, 1.0e-6, 60.0, 1.0);
    // create perfect range measurements
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurementsRange = EstimationTestUtils.createMeasurements(propagator, new RangeMeasurementCreator(context), 1.0, 3.0, 300.0);
    final List<ObservedMeasurement<?>> measurementsRangeRate = EstimationTestUtils.createMeasurements(propagator, new RangeRateMeasurementCreator(context, false), 1.0, 3.0, 300.0);
    // concat measurements
    final List<ObservedMeasurement<?>> measurements = new ArrayList<ObservedMeasurement<?>>();
    measurements.addAll(measurementsRange);
    measurements.addAll(measurementsRangeRate);
    // create orbit estimator
    final BatchLSEstimator estimator = new BatchLSEstimator(new LevenbergMarquardtOptimizer(), propagatorBuilder);
    for (final ObservedMeasurement<?> meas : measurements) {
        estimator.addMeasurement(meas);
    }
    estimator.setParametersConvergenceThreshold(1.0e-3);
    estimator.setMaxIterations(10);
    estimator.setMaxEvaluations(20);
    // we have low correlation between the two types of measurement. We can expect a good estimate.
    EstimationTestUtils.checkFit(context, estimator, 1, 2, 0.0, 0.16, 0.0, 0.40, 0.0, 2.1e-3, 0.0, 8.1e-7);
}

Example 4 with RangeRateMeasurementCreator

use of org.orekit.estimation.measurements.RangeRateMeasurementCreator in project Orekit by CS-SI.

the class KalmanEstimatorTest method testKeplerianRangeAzElAndRangeRate.

/**
 * Perfect Range, Azel and range rate measurements with a biased start
 *  Start: position/velocity biased with: [+1000,0,0] m and [0,0,0.01] m/s
 *  Keplerian formalism
 */
@Test
public void testKeplerianRangeAzElAndRangeRate() throws OrekitException {
    // Create context
    Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
    // Create initial orbit and propagator builder
    final OrbitType orbitType = OrbitType.KEPLERIAN;
    final PositionAngle positionAngle = PositionAngle.TRUE;
    final boolean perfectStart = true;
    final double minStep = 1.e-6;
    final double maxStep = 60.;
    final double dP = 1.;
    final NumericalPropagatorBuilder measPropagatorBuilder = context.createBuilder(orbitType, positionAngle, perfectStart, minStep, maxStep, dP);
    // Create perfect range measurements
    final Propagator rangePropagator = EstimationTestUtils.createPropagator(context.initialOrbit, measPropagatorBuilder);
    final List<ObservedMeasurement<?>> rangeMeasurements = EstimationTestUtils.createMeasurements(rangePropagator, new RangeMeasurementCreator(context), 0.0, 4.0, 300.0);
    // Create perfect az/el measurements
    final Propagator angularPropagator = EstimationTestUtils.createPropagator(context.initialOrbit, measPropagatorBuilder);
    final List<ObservedMeasurement<?>> angularMeasurements = EstimationTestUtils.createMeasurements(angularPropagator, new AngularAzElMeasurementCreator(context), 0.0, 4.0, 500.0);
    // Create perfect range rate measurements
    final Propagator rangeRatePropagator = EstimationTestUtils.createPropagator(context.initialOrbit, measPropagatorBuilder);
    final List<ObservedMeasurement<?>> rangeRateMeasurements = EstimationTestUtils.createMeasurements(rangeRatePropagator, new RangeRateMeasurementCreator(context, false), 0.0, 4.0, 700.0);
    // Concatenate measurements
    final List<ObservedMeasurement<?>> measurements = new ArrayList<ObservedMeasurement<?>>();
    measurements.addAll(rangeMeasurements);
    measurements.addAll(angularMeasurements);
    measurements.addAll(rangeRateMeasurements);
    measurements.sort(new ChronologicalComparator());
    // Reference propagator for estimation performances
    final NumericalPropagator referencePropagator = measPropagatorBuilder.buildPropagator(measPropagatorBuilder.getSelectedNormalizedParameters());
    // Reference position/velocity at last measurement date
    final Orbit refOrbit = referencePropagator.propagate(measurements.get(measurements.size() - 1).getDate()).getOrbit();
    // Biased propagator for the Kalman
    final NumericalPropagatorBuilder propagatorBuilder = context.createBuilder(orbitType, positionAngle, false, minStep, maxStep, dP);
    // Cartesian covariance matrix initialization
    // Initial sigmas: 1000m on position, 0.01m/s on velocity
    final RealMatrix cartesianP = MatrixUtils.createRealDiagonalMatrix(new double[] { 1e6, 1e6, 1e6, 1e-4, 1e-4, 1e-4 });
    // Jacobian of the orbital parameters w/r to Cartesian
    final Orbit initialOrbit = orbitType.convertType(context.initialOrbit);
    final double[][] dYdC = new double[6][6];
    initialOrbit.getJacobianWrtCartesian(positionAngle, dYdC);
    final RealMatrix Jac = MatrixUtils.createRealMatrix(dYdC);
    // Orbital initial covariance matrix
    final RealMatrix initialP = Jac.multiply(cartesianP.multiply(Jac.transpose()));
    // Process noise matrix
    final RealMatrix cartesianQ = MatrixUtils.createRealDiagonalMatrix(new double[] { 1.e-4, 1.e-4, 1.e-4, 1.e-10, 1.e-10, 1.e-10 });
    final RealMatrix Q = Jac.multiply(cartesianQ.multiply(Jac.transpose()));
    // Build the Kalman filter
    final KalmanEstimatorBuilder kalmanBuilder = new KalmanEstimatorBuilder();
    kalmanBuilder.builder(propagatorBuilder);
    kalmanBuilder.estimatedMeasurementsParameters(new ParameterDriversList());
    kalmanBuilder.initialCovarianceMatrix(initialP);
    kalmanBuilder.processNoiseMatrixProvider(new ConstantProcessNoise(Q));
    final KalmanEstimator kalman = kalmanBuilder.build();
    // Filter the measurements and check the results
    final double expectedDeltaPos = 0.;
    final double posEps = 2.91e-2;
    final double expectedDeltaVel = 0.;
    final double velEps = 5.52e-6;
    final double[] expectedSigmasPos = { 1.747570, 0.666879, 1.696182 };
    final double sigmaPosEps = 1e-6;
    final double[] expectedSigmasVel = { 5.413666e-4, 4.088359e-4, 4.315316e-4 };
    final double sigmaVelEps = 1e-10;
    EstimationTestUtils.checkKalmanFit(context, kalman, measurements, refOrbit, positionAngle, expectedDeltaPos, posEps, expectedDeltaVel, velEps, expectedSigmasPos, sigmaPosEps, expectedSigmasVel, sigmaVelEps);
}

Example 5 with RangeRateMeasurementCreator

use of org.orekit.estimation.measurements.RangeRateMeasurementCreator in project Orekit by CS-SI.

the class KalmanEstimatorTest method testKeplerianRangeAndRangeRate.

/**
 * Perfect range and range rate measurements with a perfect start
 * @throws OrekitException
 */
@Test
public void testKeplerianRangeAndRangeRate() throws OrekitException {
    // Create context
    Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
    // Create initial orbit and propagator builder
    final OrbitType orbitType = OrbitType.KEPLERIAN;
    final PositionAngle positionAngle = PositionAngle.TRUE;
    final boolean perfectStart = true;
    final double minStep = 1.e-6;
    final double maxStep = 60.;
    final double dP = 1.;
    final NumericalPropagatorBuilder propagatorBuilder = context.createBuilder(orbitType, positionAngle, perfectStart, minStep, maxStep, dP);
    // Create perfect range & range rate measurements
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurementsRange = EstimationTestUtils.createMeasurements(propagator, new RangeMeasurementCreator(context), 1.0, 3.0, 300.0);
    final List<ObservedMeasurement<?>> measurementsRangeRate = EstimationTestUtils.createMeasurements(propagator, new RangeRateMeasurementCreator(context, false), 1.0, 3.0, 300.0);
    // Concatenate measurements
    final List<ObservedMeasurement<?>> measurements = new ArrayList<ObservedMeasurement<?>>();
    measurements.addAll(measurementsRange);
    measurements.addAll(measurementsRangeRate);
    // Reference propagator for estimation performances
    final NumericalPropagator referencePropagator = propagatorBuilder.buildPropagator(propagatorBuilder.getSelectedNormalizedParameters());
    // Reference position/velocity at last measurement date
    final Orbit refOrbit = referencePropagator.propagate(measurements.get(measurements.size() - 1).getDate()).getOrbit();
    // Cartesian covariance matrix initialization
    // 100m on position / 1e-2m/s on velocity
    final RealMatrix cartesianP = MatrixUtils.createRealDiagonalMatrix(new double[] { 1e-2, 1e-2, 1e-2, 1e-8, 1e-8, 1e-8 });
    // Jacobian of the orbital parameters w/r to Cartesian
    final Orbit initialOrbit = orbitType.convertType(context.initialOrbit);
    final double[][] dYdC = new double[6][6];
    initialOrbit.getJacobianWrtCartesian(PositionAngle.TRUE, dYdC);
    final RealMatrix Jac = MatrixUtils.createRealMatrix(dYdC);
    // Keplerian initial covariance matrix
    final RealMatrix initialP = Jac.multiply(cartesianP.multiply(Jac.transpose()));
    // Process noise matrix
    final RealMatrix cartesianQ = MatrixUtils.createRealDiagonalMatrix(new double[] { 1.e-4, 1.e-4, 1.e-4, 1.e-10, 1.e-10, 1.e-10 });
    final RealMatrix Q = Jac.multiply(cartesianQ.multiply(Jac.transpose()));
    // Build the Kalman filter
    final KalmanEstimatorBuilder kalmanBuilder = new KalmanEstimatorBuilder();
    kalmanBuilder.builder(propagatorBuilder);
    kalmanBuilder.estimatedMeasurementsParameters(new ParameterDriversList());
    kalmanBuilder.initialCovarianceMatrix(initialP);
    kalmanBuilder.processNoiseMatrixProvider(new ConstantProcessNoise(Q));
    final KalmanEstimator kalman = kalmanBuilder.build();
    // Filter the measurements and check the results
    final double expectedDeltaPos = 0.;
    final double posEps = 5.96e-3;
    final double expectedDeltaVel = 0.;
    final double velEps = 2.06e-6;
    final double[] expectedSigmasPos = { 0.341538, 8.175281, 4.634384 };
    final double sigmaPosEps = 1e-6;
    final double[] expectedSigmasVel = { 1.167838e-3, 1.036437e-3, 2.834385e-3 };
    final double sigmaVelEps = 1e-9;
    EstimationTestUtils.checkKalmanFit(context, kalman, measurements, refOrbit, positionAngle, expectedDeltaPos, posEps, expectedDeltaVel, velEps, expectedSigmasPos, sigmaPosEps, expectedSigmasVel, sigmaVelEps);
}