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1   /*
2    * Licensed to the Hipparchus project under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The Hipparchus project 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    *      https://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  
18  package org.hipparchus.filtering.kalman.linear;
19  
20  import org.hipparchus.linear.RealMatrix;
21  import org.hipparchus.linear.RealVector;
22  
23  /**
24   * Container for {@link LinearProcess linear process} evolution data.
25   * @see LinearProcess
26   * @since 1.3
27   */
28  public class LinearEvolution {
29  
30      /** State transition matrix A<sub>k-1</sub>. */
31      private final RealMatrix stateTransitionMatrix;
32  
33      /** Control matrix B<sub>k-1</sub> (can be null if the process is not controlled). */
34      private final RealMatrix controlMatrix;
35  
36      /** Command u<sub>k-1</sub>. (can be null if the process is not controlled). */
37      private final RealVector command;
38  
39      /** Process noise matrix Q<sub>k-1</sub>. */
40      private final RealMatrix processNoiseMatrix;
41  
42      /** Jacobian of the measurement with respect to the state (may be null). */
43      private final RealMatrix measurementJacobian;
44  
45      /** Simple constructor.
46       * @param stateTransitionMatrix state transition matrix A<sub>k-1</sub>
47       * @param controlMatrix control matrix B<sub>k-1</sub> (can be null if the process is not controlled)
48       * @param command u<sub>k-1</sub>. (can be null if the process is not controlled)
49       * @param processNoiseMatrix process noise matrix Q<sub>k-1</sub>
50       * @param measurementJacobian Jacobian of the measurement with respect to the state
51       * (may be null if measurement should be ignored)
52       */
53      public LinearEvolution(final RealMatrix stateTransitionMatrix,
54                             final RealMatrix controlMatrix, final RealVector command,
55                             final RealMatrix processNoiseMatrix,
56                             final RealMatrix measurementJacobian) {
57          this.stateTransitionMatrix = stateTransitionMatrix;
58          this.controlMatrix         = controlMatrix;
59          this.command               = command;
60          this.processNoiseMatrix    = processNoiseMatrix;
61          this.measurementJacobian   = measurementJacobian;
62      }
63  
64      /** Get the state transition matrix A<sub>k-1</sub>.
65       * @return state transition matrix A<sub>k-1</sub>
66       */
67      public RealMatrix getStateTransitionMatrix() {
68          return stateTransitionMatrix;
69      }
70  
71      /** Get the control matrix B<sub>k-1</sub>.
72       * @return control matrix B<sub>k-1</sub> (can be null if there is no control)
73       */
74      public RealMatrix getControlMatrix() {
75          return controlMatrix;
76      }
77  
78      /** Get the command u<sub>k-1</sub>.
79       * @return command vector u<sub>k-1</sub> (can be null if there is no control)
80       */
81      public RealVector getCommand() {
82          return command;
83      }
84  
85      /** Get the process noise matrix Q<sub>k-1</sub>.
86       * @return process noise matrix<sub>k-1</sub>
87       */
88      public RealMatrix getProcessNoiseMatrix() {
89          return processNoiseMatrix;
90      }
91  
92      /** Get measurement Jacobian.
93       * @return Jacobian of the measurement with respect to the state
94       * (may be null if measurement should be ignored)
95       */
96      public RealMatrix getMeasurementJacobian() {
97          return measurementJacobian;
98      }
99  
100 }