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    *   http://www.apache.org/licenses/LICENSE-2.0
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   * Unless required by applicable law or agreed to in writing, software
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  package org.orekit.estimation.sequential;
  
  import java.util.List;
  
  import org.hipparchus.linear.MatrixUtils;
  import org.hipparchus.linear.RealMatrix;
  import org.junit.jupiter.api.Test;
  import org.orekit.estimation.BrouwerLyddaneContext;
  import org.orekit.estimation.BrouwerLyddaneEstimationTestUtils;
  import org.orekit.estimation.measurements.ObservedMeasurement;
  import org.orekit.estimation.measurements.PVMeasurementCreator;
  import org.orekit.orbits.Orbit;
  import org.orekit.orbits.PositionAngleType;
  import org.orekit.propagation.Propagator;
  import org.orekit.propagation.conversion.BrouwerLyddanePropagatorBuilder;
  
  public class BrouwerLyddaneKalmanEstimatorTest {
  
      /**
       * Perfect PV measurements with a perfect start
       * Keplerian formalism
       */
      @Test
      public void testKeplerianPV() {
  
          // Create context
          BrouwerLyddaneContext context = BrouwerLyddaneEstimationTestUtils.eccentricContext("regular-data:potential:tides");
  
          // Create initial orbit and propagator builder
          final PositionAngleType positionAngleType = PositionAngleType.TRUE;
          final boolean       perfectStart  = true;
          final double        dP            = 1.;
          final BrouwerLyddanePropagatorBuilder propagatorBuilder =
                          context.createBuilder(positionAngleType, perfectStart, dP);
  
          // Create perfect PV measurements
          final Propagator propagator = BrouwerLyddaneEstimationTestUtils.createPropagator(context.initialOrbit,
                                                                             propagatorBuilder);
          final List<ObservedMeasurement<?>> measurements =
                          BrouwerLyddaneEstimationTestUtils.createMeasurements(propagator,
                                                                 new PVMeasurementCreator(),
                                                                 0.0, 3.0, 300.0);
          // Reference propagator for estimation performances
          final Propagator referencePropagator = propagatorBuilder.buildPropagator();
  
          // Reference position/velocity at last measurement date
          final Orbit refOrbit = referencePropagator.
                          propagate(measurements.get(measurements.size()-1).getDate()).getOrbit();
  
          // Covariance matrix initialization
          final RealMatrix initialP = MatrixUtils.createRealDiagonalMatrix(new double [] {
              1e-2, 1e-2, 1e-2, 1e-5, 1e-5, 1e-5
          });
  
          // Process noise matrix
          RealMatrix Q = MatrixUtils.createRealDiagonalMatrix(new double [] {
              1.e-8, 1.e-8, 1.e-8, 1.e-8, 1.e-8, 1.e-8
          });
  
  
          // Build the Kalman filter
          final KalmanEstimator kalman = new KalmanEstimatorBuilder().
                          addPropagationConfiguration(propagatorBuilder, new ConstantProcessNoise(initialP, Q)).
                          build();
  
          // Filter the measurements and check the results
          final double   expectedDeltaPos  = 0.;
          final double   posEps            = 3.1e-7;
          final double   expectedDeltaVel  = 0.;
          final double   velEps            = 7.6e-10;
          final double[] expectedsigmasPos = {0.998881, 0.933806, 0.997357};
          final double   sigmaPosEps       = 1e-6;
          final double[] expectedSigmasVel = {9.475735e-4, 9.904680e-4, 5.060067e-4};
          final double   sigmaVelEps       = 1e-10;
          BrouwerLyddaneEstimationTestUtils.checkKalmanFit(context, kalman, measurements,
                                                           refOrbit, positionAngleType,
                                                           expectedDeltaPos, posEps,
                                                           expectedDeltaVel, velEps,
                                                           expectedsigmasPos, sigmaPosEps,
                                                           expectedSigmasVel, sigmaVelEps);
      }
  
  }