1 /* Copyright 2002-2021 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.ArrayList;
20 import java.util.List;
21
22 import org.hipparchus.linear.MatrixDecomposer;
23 import org.hipparchus.linear.QRDecomposer;
24 import org.orekit.errors.OrekitException;
25 import org.orekit.errors.OrekitMessages;
26 import org.orekit.propagation.conversion.OrbitDeterminationPropagatorBuilder;
27 import org.orekit.utils.ParameterDriversList;
28
29 /** Builder for a Kalman filter estimator.
30 * @author Romain Gerbaud
31 * @author Maxime Journot
32 * @since 9.2
33 */
34 public class KalmanEstimatorBuilder {
35
36 /** Decomposer to use for the correction phase. */
37 private MatrixDecomposer decomposer;
38
39 /** Builders for propagators. */
40 private List<OrbitDeterminationPropagatorBuilder> propagatorBuilders;
41
42 /** Estimated measurements parameters. */
43 private ParameterDriversList estimatedMeasurementsParameters;
44
45 /** Process noise matrices providers. */
46 private List<CovarianceMatrixProvider> processNoiseMatricesProviders;
47
48 /** Process noise matrix provider for measurement parameters. */
49 private CovarianceMatrixProvider measurementProcessNoiseMatrix;
50
51 /** Default constructor.
52 * Set an extended Kalman filter, with linearized covariance prediction.
53 */
54 public KalmanEstimatorBuilder() {
55 this.decomposer = new QRDecomposer(1.0e-15);
56 this.propagatorBuilders = new ArrayList<>();
57 this.estimatedMeasurementsParameters = new ParameterDriversList();
58 this.processNoiseMatricesProviders = new ArrayList<>();
59 this.measurementProcessNoiseMatrix = null;
60 }
61
62 /** Construct a {@link KalmanEstimator} from the data in this builder.
63 * <p>
64 * Before this method is called, {@link #addPropagationConfiguration(OrbitDeterminationPropagatorBuilder,
65 * CovarianceMatrixProvider) addPropagationConfiguration()} must have been called
66 * at least once, otherwise configuration is incomplete and an exception will be raised.
67 * </p>
68 * @return a new {@link KalmanEstimator}.
69 */
70 public KalmanEstimator build() {
71 final int n = propagatorBuilders.size();
72 if (n == 0) {
73 throw new OrekitException(OrekitMessages.NO_PROPAGATOR_CONFIGURED);
74 }
75 return new KalmanEstimator(decomposer, propagatorBuilders, processNoiseMatricesProviders,
76 estimatedMeasurementsParameters, measurementProcessNoiseMatrix);
77 }
78
79 /** Configure the matrix decomposer.
80 * @param matrixDecomposer decomposer to use for the correction phase
81 * @return this object.
82 */
83 public KalmanEstimatorBuilder decomposer(final MatrixDecomposer matrixDecomposer) {
84 decomposer = matrixDecomposer;
85 return this;
86 }
87
88 /** Add a propagation configuration.
89 * <p>
90 * This method must be called once for each propagator to managed with the
91 * {@link KalmanEstimator Kalman estimator}. The propagators order in the
92 * Kalman filter will be the call order.
93 * </p>
94 * <p>
95 * The {@code provider} should return a matrix with dimensions and ordering
96 * consistent with the {@code builder} configuration. The first 6 rows/columns
97 * correspond to the 6 orbital parameters which must all be present, regardless
98 * of the fact they are estimated or not. The remaining elements correspond
99 * to the subset of propagation parameters that are estimated, in the
100 * same order as propagatorBuilder.{@link
101 * org.orekit.propagation.conversion.PropagatorBuilder#getPropagationParametersDrivers()
102 * getPropagationParametersDrivers()}.{@link org.orekit.utils.ParameterDriversList#getDrivers()
103 * getDrivers()} (but filtering out the non selected drivers).
104 * </p>
105 * @param builder The propagator builder to use in the Kalman filter.
106 * @param provider The process noise matrices provider to use, consistent with the builder.
107 * @return this object.
108 * @see CovarianceMatrixProvider#getProcessNoiseMatrix(org.orekit.propagation.SpacecraftState,
109 * org.orekit.propagation.SpacecraftState) getProcessNoiseMatrix(previous, current)
110 */
111 public KalmanEstimatorBuilder addPropagationConfiguration(final OrbitDeterminationPropagatorBuilder builder,
112 final CovarianceMatrixProvider provider) {
113 propagatorBuilders.add(builder);
114 processNoiseMatricesProviders.add(provider);
115 return this;
116 }
117
118 /** Configure the estimated measurement parameters.
119 * <p>
120 * If this method is not called, no measurement parameters will be estimated.
121 * </p>
122 * @param estimatedMeasurementsParams The estimated measurements' parameters list.
123 * @param provider covariance matrix provider for the estimated measurement parameters
124 * @return this object.
125 * @since 10.3
126 */
127 public KalmanEstimatorBuilder estimatedMeasurementsParameters(final ParameterDriversList estimatedMeasurementsParams,
128 final CovarianceMatrixProvider provider) {
129 estimatedMeasurementsParameters = estimatedMeasurementsParams;
130 measurementProcessNoiseMatrix = provider;
131 return this;
132 }
133
134 }