1 /* Copyright 2002-2022 CS GROUP
2 * Licensed to CS GROUP (CS) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * CS licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.orekit.estimation.sequential;
18
19 import java.util.List;
20
21 import org.orekit.annotation.DefaultDataContext;
22 import org.orekit.propagation.MatricesHarvester;
23 import org.orekit.propagation.PropagationType;
24 import org.orekit.propagation.Propagator;
25 import org.orekit.propagation.analytical.tle.TLEJacobiansMapper;
26 import org.orekit.propagation.analytical.tle.TLEPropagator;
27 import org.orekit.propagation.conversion.OrbitDeterminationPropagatorBuilder;
28 import org.orekit.utils.ParameterDriversList;
29
30 /** Class defining the process model dynamics to use with a {@link KalmanEstimator}.
31 * <p>
32 * This class is an adaption of the {@link KalmanModel} class
33 * but for the {@link TLEPropagator TLE propagator}.
34 * </p>
35 * @author Romain Gerbaud
36 * @author Maxime Journot
37 * @author Bryan Cazabonne
38 * @author Thomas Paulet
39 * @since 11.0
40 * @deprecated as of 11.1, replaced by {@link KalmanModel}
41 */
42 @Deprecated
43 public class TLEKalmanModel extends AbstractKalmanModel {
44
45 /** Kalman process model constructor (package private).
46 * @param propagatorBuilders propagators builders used to evaluate the orbits.
47 * @param covarianceMatricesProviders providers for covariance matrices
48 * @param estimatedMeasurementParameters measurement parameters to estimate
49 * @param measurementProcessNoiseMatrix provider for measurement process noise matrix
50 */
51 public TLEKalmanModel(final List<OrbitDeterminationPropagatorBuilder> propagatorBuilders,
52 final List<CovarianceMatrixProvider> covarianceMatricesProviders,
53 final ParameterDriversList estimatedMeasurementParameters,
54 final CovarianceMatrixProvider measurementProcessNoiseMatrix) {
55 // call super constructor
56 super(propagatorBuilders, covarianceMatricesProviders, estimatedMeasurementParameters,
57 measurementProcessNoiseMatrix, new TLEJacobiansMapper[propagatorBuilders.size()]);
58 }
59
60 /** {@inheritDoc} */
61 @Override
62 @DefaultDataContext
63 protected void updateReferenceTrajectories(final Propagator[] propagators,
64 final PropagationType pType,
65 final PropagationType sType) {
66
67 // Update the reference trajectory propagator
68 setReferenceTrajectories(propagators);
69
70 // Jacobian harvesters
71 final MatricesHarvester[] harvesters = new MatricesHarvester[propagators.length];
72
73 for (int k = 0; k < propagators.length; ++k) {
74 // Link the partial derivatives to this new propagator
75 final String equationName = KalmanEstimator.class.getName() + "-derivatives-" + k;
76 harvesters[k] = ((TLEPropagator) getReferenceTrajectories()[k]).setupMatricesComputation(equationName, null, null);
77 }
78
79 // Update Jacobian harvesters
80 setHarvesters(harvesters);
81
82 }
83
84 }