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

Example 31 with ObservedMeasurement

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

the class KalmanOrbitDeterminationTest method run.

/**
 * Function running the Kalman filter estimation.
 * @param input Input configuration file
 * @param orbitType Orbit type to use (calculation and display)
 * @param print Choose whether the results are printed on console or not
 * @param cartesianOrbitalP Orbital part of the initial covariance matrix in Cartesian formalism
 * @param cartesianOrbitalQ Orbital part of the process noise matrix in Cartesian formalism
 * @param propagationP Propagation part of the initial covariance matrix
 * @param propagationQ Propagation part of the process noise matrix
 * @param measurementP Measurement part of the initial covariance matrix
 * @param measurementQ Measurement part of the process noise matrix
 */
private ResultKalman run(final File input, final OrbitType orbitType, final boolean print, final RealMatrix cartesianOrbitalP, final RealMatrix cartesianOrbitalQ, final RealMatrix propagationP, final RealMatrix propagationQ, final RealMatrix measurementP, final RealMatrix measurementQ) throws IOException, IllegalArgumentException, OrekitException, ParseException {
    // Read input parameters
    KeyValueFileParser<ParameterKey> parser = new KeyValueFileParser<ParameterKey>(ParameterKey.class);
    parser.parseInput(input.getAbsolutePath(), new FileInputStream(input));
    // Log files
    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
    Orbit initialGuess = createOrbit(parser, gravityField.getMu());
    // Convert to desired orbit type
    initialGuess = orbitType.convertType(initialGuess);
    // 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);
    // 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)));
    }
    // Building the Kalman filter:
    // - Gather the estimated measurement parameters in a list
    // - Prepare the initial covariance matrix and the process noise matrix
    // - Build the Kalman filter
    // --------------------------------------------------------------------
    // Build the list of estimated measurements
    final ParameterDriversList estimatedMeasurementsParameters = new ParameterDriversList();
    for (ObservedMeasurement<?> measurement : measurements) {
        final List<ParameterDriver> drivers = measurement.getParametersDrivers();
        for (ParameterDriver driver : drivers) {
            if (driver.isSelected()) {
                // Add the driver
                estimatedMeasurementsParameters.add(driver);
            }
        }
    }
    // Sort the list lexicographically
    estimatedMeasurementsParameters.sort();
    // Orbital covariance matrix initialization
    // Jacobian of the orbital parameters w/r to Cartesian
    final double[][] dYdC = new double[6][6];
    initialGuess.getJacobianWrtCartesian(propagatorBuilder.getPositionAngle(), dYdC);
    final RealMatrix Jac = MatrixUtils.createRealMatrix(dYdC);
    RealMatrix orbitalP = Jac.multiply(cartesianOrbitalP.multiply(Jac.transpose()));
    // Orbital process noise matrix
    RealMatrix orbitalQ = Jac.multiply(cartesianOrbitalQ.multiply(Jac.transpose()));
    // Build the full covariance matrix and process noise matrix
    final int nbPropag = (propagationP != null) ? propagationP.getRowDimension() : 0;
    final int nbMeas = (measurementP != null) ? measurementP.getRowDimension() : 0;
    final RealMatrix initialP = MatrixUtils.createRealMatrix(6 + nbPropag + nbMeas, 6 + nbPropag + nbMeas);
    final RealMatrix Q = MatrixUtils.createRealMatrix(6 + nbPropag + nbMeas, 6 + nbPropag + nbMeas);
    // Orbital part
    initialP.setSubMatrix(orbitalP.getData(), 0, 0);
    Q.setSubMatrix(orbitalQ.getData(), 0, 0);
    // Propagation part
    if (propagationP != null) {
        initialP.setSubMatrix(propagationP.getData(), 6, 6);
        Q.setSubMatrix(propagationQ.getData(), 6, 6);
    }
    // Measurement part
    if (measurementP != null) {
        initialP.setSubMatrix(measurementP.getData(), 6 + nbPropag, 6 + nbPropag);
        Q.setSubMatrix(measurementQ.getData(), 6 + nbPropag, 6 + nbPropag);
    }
    // Build the Kalman
    KalmanEstimatorBuilder kalmanBuilder = new KalmanEstimatorBuilder();
    kalmanBuilder.builder(propagatorBuilder);
    kalmanBuilder.estimatedMeasurementsParameters(estimatedMeasurementsParameters);
    kalmanBuilder.initialCovarianceMatrix(initialP);
    kalmanBuilder.processNoiseMatrixProvider(new ConstantProcessNoise(Q));
    final KalmanEstimator kalman = kalmanBuilder.build();
    // Add an observer
    kalman.setObserver(new KalmanObserver() {

        /**
         * Date of the first measurement.
         */
        private AbsoluteDate t0;

        /**
         * {@inheritDoc}
         * @throws OrekitException
         */
        @Override
        @SuppressWarnings("unchecked")
        public void evaluationPerformed(final KalmanEstimation estimation) throws OrekitException {
            // Current measurement number, date and status
            final EstimatedMeasurement<?> estimatedMeasurement = estimation.getCorrectedMeasurement();
            final int currentNumber = estimation.getCurrentMeasurementNumber();
            final AbsoluteDate currentDate = estimatedMeasurement.getDate();
            final EstimatedMeasurement.Status currentStatus = estimatedMeasurement.getStatus();
            // Current estimated measurement
            final ObservedMeasurement<?> observedMeasurement = estimatedMeasurement.getObservedMeasurement();
            // Measurement type & Station name
            String measType = "";
            String stationName = "";
            // Register the measurement in the proper measurement logger
            if (observedMeasurement instanceof Range) {
                // Add the tuple (estimation, prediction) to the log
                rangeLog.add(currentNumber, (EstimatedMeasurement<Range>) estimatedMeasurement);
                // Measurement type & Station name
                measType = "RANGE";
                stationName = ((EstimatedMeasurement<Range>) estimatedMeasurement).getObservedMeasurement().getStation().getBaseFrame().getName();
            } else if (observedMeasurement instanceof RangeRate) {
                rangeRateLog.add(currentNumber, (EstimatedMeasurement<RangeRate>) estimatedMeasurement);
                measType = "RANGE_RATE";
                stationName = ((EstimatedMeasurement<RangeRate>) estimatedMeasurement).getObservedMeasurement().getStation().getBaseFrame().getName();
            } else if (observedMeasurement instanceof AngularAzEl) {
                azimuthLog.add(currentNumber, (EstimatedMeasurement<AngularAzEl>) estimatedMeasurement);
                elevationLog.add(currentNumber, (EstimatedMeasurement<AngularAzEl>) estimatedMeasurement);
                measType = "AZ_EL";
                stationName = ((EstimatedMeasurement<AngularAzEl>) estimatedMeasurement).getObservedMeasurement().getStation().getBaseFrame().getName();
            } else if (observedMeasurement instanceof PV) {
                positionLog.add(currentNumber, (EstimatedMeasurement<PV>) estimatedMeasurement);
                velocityLog.add(currentNumber, (EstimatedMeasurement<PV>) estimatedMeasurement);
                measType = "PV";
            }
            // Header
            if (print) {
                if (currentNumber == 1) {
                    // Set t0 to first measurement date
                    t0 = currentDate;
                    // Print header
                    final String formatHeader = "%-4s\t%-25s\t%15s\t%-10s\t%-10s\t%-20s\t%20s\t%20s";
                    String header = String.format(Locale.US, formatHeader, "Nb", "Epoch", "Dt[s]", "Status", "Type", "Station", "DP Corr", "DV Corr");
                    // Orbital drivers
                    for (DelegatingDriver driver : estimation.getEstimatedOrbitalParameters().getDrivers()) {
                        header += String.format(Locale.US, "\t%20s", driver.getName());
                        header += String.format(Locale.US, "\t%20s", "D" + driver.getName());
                    }
                    // Propagation drivers
                    for (DelegatingDriver driver : estimation.getEstimatedPropagationParameters().getDrivers()) {
                        header += String.format(Locale.US, "\t%20s", driver.getName());
                        header += String.format(Locale.US, "\t%20s", "D" + driver.getName());
                    }
                    // Measurements drivers
                    for (DelegatingDriver driver : estimation.getEstimatedMeasurementsParameters().getDrivers()) {
                        header += String.format(Locale.US, "\t%20s", driver.getName());
                        header += String.format(Locale.US, "\t%20s", "D" + driver.getName());
                    }
                    // Print header
                    System.out.println(header);
                }
                // Print current measurement info in terminal
                String line = "";
                // Line format
                final String lineFormat = "%4d\t%-25s\t%15.3f\t%-10s\t%-10s\t%-20s\t%20.9e\t%20.9e";
                // Orbital correction = DP & DV between predicted orbit and estimated orbit
                final Vector3D predictedP = estimation.getPredictedSpacecraftStates()[0].getPVCoordinates().getPosition();
                final Vector3D predictedV = estimation.getPredictedSpacecraftStates()[0].getPVCoordinates().getVelocity();
                final Vector3D estimatedP = estimation.getCorrectedSpacecraftStates()[0].getPVCoordinates().getPosition();
                final Vector3D estimatedV = estimation.getCorrectedSpacecraftStates()[0].getPVCoordinates().getVelocity();
                final double DPcorr = Vector3D.distance(predictedP, estimatedP);
                final double DVcorr = Vector3D.distance(predictedV, estimatedV);
                line = String.format(Locale.US, lineFormat, currentNumber, currentDate.toString(), currentDate.durationFrom(t0), currentStatus.toString(), measType, stationName, DPcorr, DVcorr);
                // Handle parameters printing (value and error)
                int jPar = 0;
                final RealMatrix Pest = estimation.getPhysicalEstimatedCovarianceMatrix();
                // Orbital drivers
                for (DelegatingDriver driver : estimation.getEstimatedOrbitalParameters().getDrivers()) {
                    line += String.format(Locale.US, "\t%20.9f", driver.getValue());
                    line += String.format(Locale.US, "\t%20.9e", FastMath.sqrt(Pest.getEntry(jPar, jPar)));
                    jPar++;
                }
                // Propagation drivers
                for (DelegatingDriver driver : estimation.getEstimatedPropagationParameters().getDrivers()) {
                    line += String.format(Locale.US, "\t%20.9f", driver.getValue());
                    line += String.format(Locale.US, "\t%20.9e", FastMath.sqrt(Pest.getEntry(jPar, jPar)));
                    jPar++;
                }
                // Measurements drivers
                for (DelegatingDriver driver : estimatedMeasurementsParameters.getDrivers()) {
                    line += String.format(Locale.US, "\t%20.9f", driver.getValue());
                    line += String.format(Locale.US, "\t%20.9e", FastMath.sqrt(Pest.getEntry(jPar, jPar)));
                    jPar++;
                }
                // Print the line
                System.out.println(line);
            }
        }
    });
    // Process the list measurements
    final Orbit estimated = kalman.processMeasurements(measurements).getInitialState().getOrbit();
    // Get the last estimated physical covariances
    final RealMatrix covarianceMatrix = kalman.getPhysicalEstimatedCovarianceMatrix();
    // Parameters and measurements.
    final ParameterDriversList propagationParameters = kalman.getPropagationParametersDrivers(true);
    final ParameterDriversList measurementsParameters = kalman.getEstimatedMeasurementsParameters();
    // Eventually, print parameter changes, statistics and covariances
    if (print) {
        // Display parameter change for non orbital drivers
        int length = 0;
        for (final ParameterDriver parameterDriver : propagationParameters.getDrivers()) {
            length = FastMath.max(length, parameterDriver.getName().length());
        }
        for (final ParameterDriver parameterDriver : measurementsParameters.getDrivers()) {
            length = FastMath.max(length, parameterDriver.getName().length());
        }
        if (propagationParameters.getNbParams() > 0) {
            displayParametersChanges(System.out, "Estimated propagator parameters changes: ", true, length, propagationParameters);
        }
        if (measurementsParameters.getNbParams() > 0) {
            displayParametersChanges(System.out, "Estimated measurements parameters changes: ", true, length, measurementsParameters);
        }
        // Measurements statistics summary
        System.out.println("");
        rangeLog.displaySummary(System.out);
        rangeRateLog.displaySummary(System.out);
        azimuthLog.displaySummary(System.out);
        elevationLog.displaySummary(System.out);
        positionLog.displaySummary(System.out);
        velocityLog.displaySummary(System.out);
        // Covariances and sigmas
        displayFinalCovariances(System.out, kalman);
    }
    // Instantiation of the results
    return new ResultKalman(propagationParameters, measurementsParameters, kalman.getCurrentMeasurementNumber(), estimated.getPVCoordinates(), rangeLog.createStatisticsSummary(), rangeRateLog.createStatisticsSummary(), azimuthLog.createStatisticsSummary(), elevationLog.createStatisticsSummary(), positionLog.createStatisticsSummary(), velocityLog.createStatisticsSummary(), covarianceMatrix);
}

Example 32 with ObservedMeasurement

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

the class BatchLSEstimatorTest method testKeplerRange.

/**
 * Perfect range measurements with a biased start
 * @throws OrekitException
 */
@Test
public void testKeplerRange() 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<?>> measurements = EstimationTestUtils.createMeasurements(propagator, new RangeMeasurementCreator(context), 1.0, 3.0, 300.0);
    // create orbit estimator
    final BatchLSEstimator estimator = new BatchLSEstimator(new LevenbergMarquardtOptimizer(), propagatorBuilder);
    for (final ObservedMeasurement<?> range : measurements) {
        estimator.addMeasurement(range);
    }
    estimator.setParametersConvergenceThreshold(1.0e-2);
    estimator.setMaxIterations(10);
    estimator.setMaxEvaluations(20);
    estimator.setObserver(new BatchLSObserver() {

        int lastIter = 0;

        int lastEval = 0;

        /**
         * {@inheritDoc}
         */
        @Override
        public void evaluationPerformed(int iterationsCount, int evaluationscount, Orbit[] orbits, ParameterDriversList estimatedOrbitalParameters, ParameterDriversList estimatedPropagatorParameters, ParameterDriversList estimatedMeasurementsParameters, EstimationsProvider evaluationsProvider, Evaluation lspEvaluation) throws OrekitException {
            if (iterationsCount == lastIter) {
                Assert.assertEquals(lastEval + 1, evaluationscount);
            } else {
                Assert.assertEquals(lastIter + 1, iterationsCount);
            }
            lastIter = iterationsCount;
            lastEval = evaluationscount;
            Assert.assertEquals(measurements.size(), evaluationsProvider.getNumber());
            try {
                evaluationsProvider.getEstimatedMeasurement(-1);
                Assert.fail("an exception should have been thrown");
            } catch (OrekitException oe) {
                Assert.assertEquals(LocalizedCoreFormats.OUT_OF_RANGE_SIMPLE, oe.getSpecifier());
            }
            try {
                evaluationsProvider.getEstimatedMeasurement(measurements.size());
                Assert.fail("an exception should have been thrown");
            } catch (OrekitException oe) {
                Assert.assertEquals(LocalizedCoreFormats.OUT_OF_RANGE_SIMPLE, oe.getSpecifier());
            }
            AbsoluteDate previous = AbsoluteDate.PAST_INFINITY;
            for (int i = 0; i < evaluationsProvider.getNumber(); ++i) {
                AbsoluteDate current = evaluationsProvider.getEstimatedMeasurement(i).getDate();
                Assert.assertTrue(current.compareTo(previous) >= 0);
                previous = current;
            }
        }
    });
    ParameterDriver aDriver = estimator.getOrbitalParametersDrivers(true).getDrivers().get(0);
    Assert.assertEquals("a", aDriver.getName());
    aDriver.setValue(aDriver.getValue() + 1.2);
    aDriver.setReferenceDate(AbsoluteDate.GALILEO_EPOCH);
    EstimationTestUtils.checkFit(context, estimator, 2, 3, 0.0, 1.1e-6, 0.0, 2.8e-6, 0.0, 4.0e-7, 0.0, 2.2e-10);
    // got a default one
    for (final ParameterDriver driver : estimator.getOrbitalParametersDrivers(true).getDrivers()) {
        if ("a".equals(driver.getName())) {
            // user-specified reference date
            Assert.assertEquals(0, driver.getReferenceDate().durationFrom(AbsoluteDate.GALILEO_EPOCH), 1.0e-15);
        } else {
            // default reference date
            Assert.assertEquals(0, driver.getReferenceDate().durationFrom(propagatorBuilder.getInitialOrbitDate()), 1.0e-15);
        }
    }
}

Example 33 with ObservedMeasurement

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

the class ModelTest method testPerfectValue.

@Test
public void testPerfectValue() 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) {
            Assert.assertEquals(1, newOrbits.length);
            Assert.assertEquals(0, context.initialOrbit.getDate().durationFrom(newOrbits[0].getDate()), 1.0e-15);
            Assert.assertEquals(0, Vector3D.distance(context.initialOrbit.getPVCoordinates().getPosition(), newOrbits[0].getPVCoordinates().getPosition()), 1.0e-15);
            Assert.assertEquals(measurements.size(), newEvaluations.size());
        }
    };
    final Model model = new Model(builders, measurements, estimatedMeasurementsParameters, modelObserver);
    model.setIterationsCounter(new Incrementor(100));
    model.setEvaluationsCounter(new Incrementor(100));
    // Test forward propagation flag to true
    assertEquals(true, model.isForwardPropagation());
    // evaluate model on perfect start point
    final double[] normalizedProp = propagatorBuilder.getSelectedNormalizedParameters();
    final double[] normalized = new double[normalizedProp.length + estimatedMeasurementsParameters.getNbParams()];
    System.arraycopy(normalizedProp, 0, normalized, 0, normalizedProp.length);
    int i = normalizedProp.length;
    for (final ParameterDriver driver : estimatedMeasurementsParameters.getDrivers()) {
        normalized[i++] = driver.getNormalizedValue();
    }
    Pair<RealVector, RealMatrix> value = model.value(new ArrayRealVector(normalized));
    int index = 0;
    for (ObservedMeasurement<?> measurement : measurements) {
        for (int k = 0; k < measurement.getDimension(); ++k) {
            // the value is already a weighted residual
            Assert.assertEquals(0.0, value.getFirst().getEntry(index++), 1.6e-7);
        }
    }
    Assert.assertEquals(index, value.getFirst().getDimension());
}

Example 34 with ObservedMeasurement

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

the class OrbitDeterminationTest method readMeasurements.

/**
 * Read a measurements file.
 * @param file measurements file
 * @param stations name to stations data map
 * @param pvData PV measurements data
 * @param satRangeBias range bias due to transponder delay
 * @param weights base weights for measurements
 * @param rangeOutliersManager manager for range measurements outliers (null if none configured)
 * @param rangeRateOutliersManager manager for range-rate measurements outliers (null if none configured)
 * @param azElOutliersManager manager for azimuth-elevation measurements outliers (null if none configured)
 * @param pvOutliersManager manager for PV measurements outliers (null if none configured)
 * @return measurements list
 */
private List<ObservedMeasurement<?>> readMeasurements(final File file, final Map<String, StationData> stations, final PVData pvData, final Bias<Range> satRangeBias, final Weights weights, final OutlierFilter<Range> rangeOutliersManager, final OutlierFilter<RangeRate> rangeRateOutliersManager, final OutlierFilter<AngularAzEl> azElOutliersManager, final OutlierFilter<PV> pvOutliersManager) throws UnsupportedEncodingException, IOException, OrekitException {
    final List<ObservedMeasurement<?>> measurements = new ArrayList<ObservedMeasurement<?>>();
    BufferedReader br = null;
    try {
        br = new BufferedReader(new InputStreamReader(new FileInputStream(file), "UTF-8"));
        int lineNumber = 0;
        for (String line = br.readLine(); line != null; line = br.readLine()) {
            ++lineNumber;
            line = line.trim();
            if (line.length() > 0 && !line.startsWith("#")) {
                String[] fields = line.split("\\s+");
                if (fields.length < 2) {
                    throw new OrekitException(OrekitMessages.UNABLE_TO_PARSE_LINE_IN_FILE, lineNumber, file.getName(), line);
                }
                switch(fields[1]) {
                    case "RANGE":
                        final Range range = new RangeParser().parseFields(fields, stations, pvData, satRangeBias, weights, line, lineNumber, file.getName());
                        if (rangeOutliersManager != null) {
                            range.addModifier(rangeOutliersManager);
                        }
                        addIfNonZeroWeight(range, measurements);
                        break;
                    case "RANGE_RATE":
                        final RangeRate rangeRate = new RangeRateParser().parseFields(fields, stations, pvData, satRangeBias, weights, line, lineNumber, file.getName());
                        if (rangeOutliersManager != null) {
                            rangeRate.addModifier(rangeRateOutliersManager);
                        }
                        addIfNonZeroWeight(rangeRate, measurements);
                        break;
                    case "AZ_EL":
                        final AngularAzEl angular = new AzElParser().parseFields(fields, stations, pvData, satRangeBias, weights, line, lineNumber, file.getName());
                        if (azElOutliersManager != null) {
                            angular.addModifier(azElOutliersManager);
                        }
                        addIfNonZeroWeight(angular, measurements);
                        break;
                    case "PV":
                        final PV pv = new PVParser().parseFields(fields, stations, pvData, satRangeBias, weights, line, lineNumber, file.getName());
                        if (pvOutliersManager != null) {
                            pv.addModifier(pvOutliersManager);
                        }
                        addIfNonZeroWeight(pv, measurements);
                        break;
                    default:
                        throw new OrekitException(LocalizedCoreFormats.SIMPLE_MESSAGE, "unknown measurement type " + fields[1] + " at line " + lineNumber + " in file " + file.getName());
                }
            }
        }
    } finally {
        if (br != null) {
            br.close();
        }
    }
    if (measurements.isEmpty()) {
        throw new OrekitException(LocalizedCoreFormats.SIMPLE_MESSAGE, "not measurements read from file " + file.getAbsolutePath());
    }
    return measurements;
}

Example 35 with ObservedMeasurement

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

the class BiasTest method testEstimateBias.

@SuppressWarnings("unchecked")
@Test
public void testEstimateBias() 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
    final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit, propagatorBuilder);
    final List<ObservedMeasurement<?>> measurements = EstimationTestUtils.createMeasurements(propagator, new RangeMeasurementCreator(context), 1.0, 3.0, 300.0);
    // create range biases: one bias for each station
    final RandomGenerator random = new Well19937a(0x0c4b69da5d64b35al);
    final Bias<?>[] stationsRangeBiases = new Bias<?>[context.stations.size()];
    final double[] realStationsBiases = new double[context.stations.size()];
    for (int i = 0; i < context.stations.size(); ++i) {
        final TopocentricFrame base = context.stations.get(i).getBaseFrame();
        stationsRangeBiases[i] = new Bias<Range>(new String[] { base.getName() + " range bias" }, new double[] { 0.0 }, new double[] { 1.0 }, new double[] { Double.NEGATIVE_INFINITY }, new double[] { Double.POSITIVE_INFINITY });
        realStationsBiases[i] = 2 * random.nextDouble() - 1;
    }
    // create orbit estimator
    final BatchLSEstimator estimator = new BatchLSEstimator(new LevenbergMarquardtOptimizer(), propagatorBuilder);
    // add the measurements, with both spacecraft and stations biases
    for (final ObservedMeasurement<?> measurement : measurements) {
        final Range range = (Range) measurement;
        for (int i = 0; i < context.stations.size(); ++i) {
            if (range.getStation() == context.stations.get(i)) {
                double biasedRange = range.getObservedValue()[0] + realStationsBiases[i];
                final Range m = new Range(range.getStation(), range.getDate(), biasedRange, range.getTheoreticalStandardDeviation()[0], range.getBaseWeight()[0]);
                m.addModifier((Bias<Range>) stationsRangeBiases[i]);
                estimator.addMeasurement(m);
            }
        }
    }
    estimator.setParametersConvergenceThreshold(1.0e-3);
    estimator.setMaxIterations(10);
    estimator.setMaxEvaluations(20);
    // we want to estimate the biases
    for (Bias<?> bias : stationsRangeBiases) {
        for (final ParameterDriver driver : bias.getParametersDrivers()) {
            driver.setSelected(true);
        }
    }
    EstimationTestUtils.checkFit(context, estimator, 2, 3, 0.0, 7.2e-7, 0.0, 2.1e-6, 0.0, 3.7e-7, 0.0, 1.7e-10);
    for (int i = 0; i < stationsRangeBiases.length; ++i) {
        Assert.assertEquals(realStationsBiases[i], stationsRangeBiases[i].getParametersDrivers().get(0).getValue(), 3.3e-6);
    }
}