Examples with ParameterDriversList org.orekit.utils.ParameterDriversList used on opensource projects

Example 1 with ParameterDriversList

use of org.orekit.utils.ParameterDriversList in project Orekit by CS-SI.

the class ModelTest method testBackwardPropagation.

@Test
public void testBackwardPropagation() throws OrekitException {
    final 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);
    final NumericalPropagatorBuilder[] builders = { propagatorBuilder };
    // create perfect PV measurements
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurements = EstimationTestUtils.createMeasurements(propagator, new PVMeasurementCreator(), 0.0, -1.0, 300.0);
    final ParameterDriversList estimatedMeasurementsParameters = new ParameterDriversList();
    for (ObservedMeasurement<?> measurement : measurements) {
        for (final ParameterDriver driver : measurement.getParametersDrivers()) {
            if (driver.isSelected()) {
                estimatedMeasurementsParameters.add(driver);
            }
        }
    }
    // create model
    final ModelObserver modelObserver = new ModelObserver() {

        /**
         * {@inheritDoc}
         */
        @Override
        public void modelCalled(final Orbit[] newOrbits, final Map<ObservedMeasurement<?>, EstimatedMeasurement<?>> newEvaluations) {
        // Do nothing here
        }
    };
    final Model model = new Model(builders, measurements, estimatedMeasurementsParameters, modelObserver);
    // Test forward propagation flag to false
    assertEquals(false, model.isForwardPropagation());
}

Example 2 with ParameterDriversList

use of org.orekit.utils.ParameterDriversList in project Orekit by CS-SI.

the class OrbitDeterminationTest method run.

private ResultOD run(final File input, final boolean print) throws IOException, IllegalArgumentException, OrekitException, ParseException {
    // read input parameters
    KeyValueFileParser<ParameterKey> parser = new KeyValueFileParser<ParameterKey>(ParameterKey.class);
    parser.parseInput(input.getAbsolutePath(), new FileInputStream(input));
    // log file
    final RangeLog rangeLog = new RangeLog();
    final RangeRateLog rangeRateLog = new RangeRateLog();
    final AzimuthLog azimuthLog = new AzimuthLog();
    final ElevationLog elevationLog = new ElevationLog();
    final PositionLog positionLog = new PositionLog();
    final VelocityLog velocityLog = new VelocityLog();
    // gravity field
    GravityFieldFactory.addPotentialCoefficientsReader(new ICGEMFormatReader("eigen-5c.gfc", true));
    final NormalizedSphericalHarmonicsProvider gravityField = createGravityField(parser);
    // Orbit initial guess
    final Orbit initialGuess = createOrbit(parser, gravityField.getMu());
    // IERS conventions
    final IERSConventions conventions;
    if (!parser.containsKey(ParameterKey.IERS_CONVENTIONS)) {
        conventions = IERSConventions.IERS_2010;
    } else {
        conventions = IERSConventions.valueOf("IERS_" + parser.getInt(ParameterKey.IERS_CONVENTIONS));
    }
    // central body
    final OneAxisEllipsoid body = createBody(parser);
    // propagator builder
    final NumericalPropagatorBuilder propagatorBuilder = createPropagatorBuilder(parser, conventions, gravityField, body, initialGuess);
    // estimator
    final BatchLSEstimator estimator = createEstimator(parser, propagatorBuilder);
    // measurements
    final List<ObservedMeasurement<?>> measurements = new ArrayList<ObservedMeasurement<?>>();
    for (final String fileName : parser.getStringsList(ParameterKey.MEASUREMENTS_FILES, ',')) {
        measurements.addAll(readMeasurements(new File(input.getParentFile(), fileName), createStationsData(parser, body), createPVData(parser), createSatRangeBias(parser), createWeights(parser), createRangeOutliersManager(parser), createRangeRateOutliersManager(parser), createAzElOutliersManager(parser), createPVOutliersManager(parser)));
    }
    for (ObservedMeasurement<?> measurement : measurements) {
        estimator.addMeasurement(measurement);
    }
    if (print) {
        estimator.setObserver(new BatchLSObserver() {

            private PVCoordinates previousPV;

            {
                previousPV = initialGuess.getPVCoordinates();
                final String header = "iteration evaluations      ΔP(m)        ΔV(m/s)           RMS          nb Range    nb Range-rate  nb Angular     nb PV%n";
                System.out.format(Locale.US, header);
            }

            /**
             * {@inheritDoc}
             */
            @Override
            public void evaluationPerformed(final int iterationsCount, final int evaluationsCount, final Orbit[] orbits, final ParameterDriversList estimatedOrbitalParameters, final ParameterDriversList estimatedPropagatorParameters, final ParameterDriversList estimatedMeasurementsParameters, final EstimationsProvider evaluationsProvider, final LeastSquaresProblem.Evaluation lspEvaluation) {
                PVCoordinates currentPV = orbits[0].getPVCoordinates();
                final String format0 = "    %2d         %2d                                 %16.12f     %s       %s     %s     %s%n";
                final String format = "    %2d         %2d      %13.6f %12.9f %16.12f     %s       %s     %s     %s%n";
                final EvaluationCounter<Range> rangeCounter = new EvaluationCounter<Range>();
                final EvaluationCounter<RangeRate> rangeRateCounter = new EvaluationCounter<RangeRate>();
                final EvaluationCounter<AngularAzEl> angularCounter = new EvaluationCounter<AngularAzEl>();
                final EvaluationCounter<PV> pvCounter = new EvaluationCounter<PV>();
                for (final Map.Entry<ObservedMeasurement<?>, EstimatedMeasurement<?>> entry : estimator.getLastEstimations().entrySet()) {
                    if (entry.getKey() instanceof Range) {
                        @SuppressWarnings("unchecked") EstimatedMeasurement<Range> evaluation = (EstimatedMeasurement<Range>) entry.getValue();
                        rangeCounter.add(evaluation);
                    } else if (entry.getKey() instanceof RangeRate) {
                        @SuppressWarnings("unchecked") EstimatedMeasurement<RangeRate> evaluation = (EstimatedMeasurement<RangeRate>) entry.getValue();
                        rangeRateCounter.add(evaluation);
                    } else if (entry.getKey() instanceof AngularAzEl) {
                        @SuppressWarnings("unchecked") EstimatedMeasurement<AngularAzEl> evaluation = (EstimatedMeasurement<AngularAzEl>) entry.getValue();
                        angularCounter.add(evaluation);
                    } else if (entry.getKey() instanceof PV) {
                        @SuppressWarnings("unchecked") EstimatedMeasurement<PV> evaluation = (EstimatedMeasurement<PV>) entry.getValue();
                        pvCounter.add(evaluation);
                    }
                }
                if (evaluationsCount == 1) {
                    System.out.format(Locale.US, format0, iterationsCount, evaluationsCount, lspEvaluation.getRMS(), rangeCounter.format(8), rangeRateCounter.format(8), angularCounter.format(8), pvCounter.format(8));
                } else {
                    System.out.format(Locale.US, format, iterationsCount, evaluationsCount, Vector3D.distance(previousPV.getPosition(), currentPV.getPosition()), Vector3D.distance(previousPV.getVelocity(), currentPV.getVelocity()), lspEvaluation.getRMS(), rangeCounter.format(8), rangeRateCounter.format(8), angularCounter.format(8), pvCounter.format(8));
                }
                previousPV = currentPV;
            }
        });
    }
    Orbit estimated = estimator.estimate()[0].getInitialState().getOrbit();
    // compute some statistics
    for (final Map.Entry<ObservedMeasurement<?>, EstimatedMeasurement<?>> entry : estimator.getLastEstimations().entrySet()) {
        if (entry.getKey() instanceof Range) {
            @SuppressWarnings("unchecked") EstimatedMeasurement<Range> evaluation = (EstimatedMeasurement<Range>) entry.getValue();
            rangeLog.add(evaluation);
        } else if (entry.getKey() instanceof RangeRate) {
            @SuppressWarnings("unchecked") EstimatedMeasurement<RangeRate> evaluation = (EstimatedMeasurement<RangeRate>) entry.getValue();
            rangeRateLog.add(evaluation);
        } else if (entry.getKey() instanceof AngularAzEl) {
            @SuppressWarnings("unchecked") EstimatedMeasurement<AngularAzEl> evaluation = (EstimatedMeasurement<AngularAzEl>) entry.getValue();
            azimuthLog.add(evaluation);
            elevationLog.add(evaluation);
        } else if (entry.getKey() instanceof PV) {
            @SuppressWarnings("unchecked") EstimatedMeasurement<PV> evaluation = (EstimatedMeasurement<PV>) entry.getValue();
            positionLog.add(evaluation);
            velocityLog.add(evaluation);
        }
    }
    // parmaters and measurements.
    final ParameterDriversList propagatorParameters = estimator.getPropagatorParametersDrivers(true);
    final ParameterDriversList measurementsParameters = estimator.getMeasurementsParametersDrivers(true);
    // instation of results
    return new ResultOD(propagatorParameters, measurementsParameters, estimator.getIterationsCount(), estimator.getEvaluationsCount(), estimated.getPVCoordinates(), rangeLog.createStatisticsSummary(), rangeRateLog.createStatisticsSummary(), azimuthLog.createStatisticsSummary(), elevationLog.createStatisticsSummary(), positionLog.createStatisticsSummary(), velocityLog.createStatisticsSummary(), estimator.getPhysicalCovariances(1.0e-10));
}

Example 3 with ParameterDriversList

use of org.orekit.utils.ParameterDriversList 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 4 with ParameterDriversList

use of org.orekit.utils.ParameterDriversList in project Orekit by CS-SI.

the class KalmanEstimatorTest method testKeplerianRangeWithOnBoardAntennaOffset.

/**
 * Perfect range measurements with a biased start and an on-board antenna range offset
 * Keplerian formalism
 * @throws OrekitException
 */
@Test
public void testKeplerianRangeWithOnBoardAntennaOffset() 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);
    propagatorBuilder.setAttitudeProvider(new LofOffset(propagatorBuilder.getFrame(), LOFType.LVLH));
    // Antenna phase center definition
    final Vector3D antennaPhaseCenter = new Vector3D(-1.2, 2.3, -0.7);
    // Create perfect range measurements with antenna offset
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurements = EstimationTestUtils.createMeasurements(propagator, new RangeMeasurementCreator(context, antennaPhaseCenter), 1.0, 3.0, 300.0);
    // Add antenna offset to the measurements
    final OnBoardAntennaRangeModifier obaModifier = new OnBoardAntennaRangeModifier(antennaPhaseCenter);
    for (final ObservedMeasurement<?> range : measurements) {
        ((Range) range).addModifier(obaModifier);
    }
    // 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();
    // Change semi-major axis of 1.2m as in the batch test
    ParameterDriver aDriver = propagatorBuilder.getOrbitalParametersDrivers().getDrivers().get(0);
    aDriver.setValue(aDriver.getValue() + 1.2);
    aDriver.setReferenceDate(AbsoluteDate.GALILEO_EPOCH);
    // Cartesian covariance matrix initialization
    // 100m on position / 1e-2m/s on velocity
    final RealMatrix cartesianP = MatrixUtils.createRealDiagonalMatrix(new double[] { 10., 10., 10., 1e-3, 1e-3, 1e-3 });
    // Jacobian of the orbital parameters w/r to Cartesian
    final Orbit initialOrbit = OrbitType.KEPLERIAN.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 is set to 0 here
    RealMatrix Q = MatrixUtils.createRealMatrix(6, 6);
    // 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 = 4.57e-3;
    final double expectedDeltaVel = 0.;
    final double velEps = 7.29e-6;
    final double[] expectedSigmasPos = { 1.105194, 0.930785, 1.254579 };
    final double sigmaPosEps = 1e-6;
    final double[] expectedSigmasVel = { 6.193718e-4, 4.088774e-4, 3.299135e-4 };
    final double sigmaVelEps = 1e-10;
    EstimationTestUtils.checkKalmanFit(context, kalman, measurements, refOrbit, positionAngle, expectedDeltaPos, posEps, expectedDeltaVel, velEps, expectedSigmasPos, sigmaPosEps, expectedSigmasVel, sigmaVelEps);
}

Example 5 with ParameterDriversList

use of org.orekit.utils.ParameterDriversList 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);
}