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41#include "_cv.h"
42
43
44CV_IMPL CvKalman*
45cvCreateKalman( int DP, int MP, int CP )
46{
47    CvKalman *kalman = 0;
48
49    CV_FUNCNAME( "cvCreateKalman" );
50
51    __BEGIN__;
52
53    if( DP <= 0 || MP <= 0 )
54        CV_ERROR( CV_StsOutOfRange,
55        "state and measurement vectors must have positive number of dimensions" );
56
57    if( CP < 0 )
58        CP = DP;
59
60    /* allocating memory for the structure */
61    CV_CALL( kalman = (CvKalman *)cvAlloc( sizeof( CvKalman )));
62    memset( kalman, 0, sizeof(*kalman));
63
64    kalman->DP = DP;
65    kalman->MP = MP;
66    kalman->CP = CP;
67
68    CV_CALL( kalman->state_pre = cvCreateMat( DP, 1, CV_32FC1 ));
69    cvZero( kalman->state_pre );
70
71    CV_CALL( kalman->state_post = cvCreateMat( DP, 1, CV_32FC1 ));
72    cvZero( kalman->state_post );
73
74    CV_CALL( kalman->transition_matrix = cvCreateMat( DP, DP, CV_32FC1 ));
75    cvSetIdentity( kalman->transition_matrix );
76
77    CV_CALL( kalman->process_noise_cov = cvCreateMat( DP, DP, CV_32FC1 ));
78    cvSetIdentity( kalman->process_noise_cov );
79
80    CV_CALL( kalman->measurement_matrix = cvCreateMat( MP, DP, CV_32FC1 ));
81    cvZero( kalman->measurement_matrix );
82
83    CV_CALL( kalman->measurement_noise_cov = cvCreateMat( MP, MP, CV_32FC1 ));
84    cvSetIdentity( kalman->measurement_noise_cov );
85
86    CV_CALL( kalman->error_cov_pre = cvCreateMat( DP, DP, CV_32FC1 ));
87
88    CV_CALL( kalman->error_cov_post = cvCreateMat( DP, DP, CV_32FC1 ));
89    cvZero( kalman->error_cov_post );
90
91    CV_CALL( kalman->gain = cvCreateMat( DP, MP, CV_32FC1 ));
92
93    if( CP > 0 )
94    {
95        CV_CALL( kalman->control_matrix = cvCreateMat( DP, CP, CV_32FC1 ));
96        cvZero( kalman->control_matrix );
97    }
98
99    CV_CALL( kalman->temp1 = cvCreateMat( DP, DP, CV_32FC1 ));
100    CV_CALL( kalman->temp2 = cvCreateMat( MP, DP, CV_32FC1 ));
101    CV_CALL( kalman->temp3 = cvCreateMat( MP, MP, CV_32FC1 ));
102    CV_CALL( kalman->temp4 = cvCreateMat( MP, DP, CV_32FC1 ));
103    CV_CALL( kalman->temp5 = cvCreateMat( MP, 1, CV_32FC1 ));
104
105#if 1
106    kalman->PosterState = kalman->state_pre->data.fl;
107    kalman->PriorState = kalman->state_post->data.fl;
108    kalman->DynamMatr = kalman->transition_matrix->data.fl;
109    kalman->MeasurementMatr = kalman->measurement_matrix->data.fl;
110    kalman->MNCovariance = kalman->measurement_noise_cov->data.fl;
111    kalman->PNCovariance = kalman->process_noise_cov->data.fl;
112    kalman->KalmGainMatr = kalman->gain->data.fl;
113    kalman->PriorErrorCovariance = kalman->error_cov_pre->data.fl;
114    kalman->PosterErrorCovariance = kalman->error_cov_post->data.fl;
115#endif
116
117    __END__;
118
119    if( cvGetErrStatus() < 0 )
120        cvReleaseKalman( &kalman );
121
122    return kalman;
123}
124
125
126CV_IMPL void
127cvReleaseKalman( CvKalman** _kalman )
128{
129    CvKalman *kalman;
130
131    CV_FUNCNAME( "cvReleaseKalman" );
132    __BEGIN__;
133
134    if( !_kalman )
135        CV_ERROR( CV_StsNullPtr, "" );
136
137    kalman = *_kalman;
138
139    /* freeing the memory */
140    cvReleaseMat( &kalman->state_pre );
141    cvReleaseMat( &kalman->state_post );
142    cvReleaseMat( &kalman->transition_matrix );
143    cvReleaseMat( &kalman->control_matrix );
144    cvReleaseMat( &kalman->measurement_matrix );
145    cvReleaseMat( &kalman->process_noise_cov );
146    cvReleaseMat( &kalman->measurement_noise_cov );
147    cvReleaseMat( &kalman->error_cov_pre );
148    cvReleaseMat( &kalman->gain );
149    cvReleaseMat( &kalman->error_cov_post );
150    cvReleaseMat( &kalman->temp1 );
151    cvReleaseMat( &kalman->temp2 );
152    cvReleaseMat( &kalman->temp3 );
153    cvReleaseMat( &kalman->temp4 );
154    cvReleaseMat( &kalman->temp5 );
155
156    memset( kalman, 0, sizeof(*kalman));
157
158    /* deallocating the structure */
159    cvFree( _kalman );
160
161    __END__;
162}
163
164
165CV_IMPL const CvMat*
166cvKalmanPredict( CvKalman* kalman, const CvMat* control )
167{
168    CvMat* result = 0;
169
170    CV_FUNCNAME( "cvKalmanPredict" );
171
172    __BEGIN__;
173
174    if( !kalman )
175        CV_ERROR( CV_StsNullPtr, "" );
176
177    /* update the state */
178    /* x'(k) = A*x(k) */
179    CV_CALL( cvMatMulAdd( kalman->transition_matrix, kalman->state_post, 0, kalman->state_pre ));
180
181    if( control && kalman->CP > 0 )
182        /* x'(k) = x'(k) + B*u(k) */
183        CV_CALL( cvMatMulAdd( kalman->control_matrix, control, kalman->state_pre, kalman->state_pre ));
184
185    /* update error covariance matrices */
186    /* temp1 = A*P(k) */
187    CV_CALL( cvMatMulAdd( kalman->transition_matrix, kalman->error_cov_post, 0, kalman->temp1 ));
188
189    /* P'(k) = temp1*At + Q */
190    CV_CALL( cvGEMM( kalman->temp1, kalman->transition_matrix, 1, kalman->process_noise_cov, 1,
191                     kalman->error_cov_pre, CV_GEMM_B_T ));
192
193    result = kalman->state_pre;
194
195    __END__;
196
197    return result;
198}
199
200
201CV_IMPL const CvMat*
202cvKalmanCorrect( CvKalman* kalman, const CvMat* measurement )
203{
204    CvMat* result = 0;
205
206    CV_FUNCNAME( "cvKalmanCorrect" );
207
208    __BEGIN__;
209
210    if( !kalman || !measurement )
211        CV_ERROR( CV_StsNullPtr, "" );
212
213    /* temp2 = H*P'(k) */
214    CV_CALL( cvMatMulAdd( kalman->measurement_matrix,
215                          kalman->error_cov_pre, 0, kalman->temp2 ));
216    /* temp3 = temp2*Ht + R */
217    CV_CALL( cvGEMM( kalman->temp2, kalman->measurement_matrix, 1,
218                     kalman->measurement_noise_cov, 1, kalman->temp3, CV_GEMM_B_T ));
219
220    /* temp4 = inv(temp3)*temp2 = Kt(k) */
221    CV_CALL( cvSolve( kalman->temp3, kalman->temp2, kalman->temp4, CV_SVD ));
222
223    /* K(k) */
224    CV_CALL( cvTranspose( kalman->temp4, kalman->gain ));
225
226    /* temp5 = z(k) - H*x'(k) */
227    CV_CALL( cvGEMM( kalman->measurement_matrix, kalman->state_pre, -1, measurement, 1, kalman->temp5 ));
228
229    /* x(k) = x'(k) + K(k)*temp5 */
230    CV_CALL( cvMatMulAdd( kalman->gain, kalman->temp5, kalman->state_pre, kalman->state_post ));
231
232    /* P(k) = P'(k) - K(k)*temp2 */
233    CV_CALL( cvGEMM( kalman->gain, kalman->temp2, -1, kalman->error_cov_pre, 1,
234                     kalman->error_cov_post, 0 ));
235
236    result = kalman->state_post;
237
238    __END__;
239
240    return result;
241}
242