main.cpp

利用OpenCV库实现的一个Kalman滤波的例子。

#include "../inc/cv.h"
#include "../inc/highgui.h"
#include <math.h>
#include <iostream.h>

int main(int argc, char** argv)
{
    /* A matrix data */
    const float A[] = { 1, 1, 0, 1 };

    IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
    CvKalman* kalman = cvCreateKalman( 2, 1, 0 );
    /* state is (phi, delta_phi) - angle and angle increment */
    CvMat* state = cvCreateMat( 2, 1, CV_32FC1 );
    CvMat* process_noise = cvCreateMat( 2, 1, CV_32FC1 );
    /* only phi (angle) is measured */
    CvMat* measurement = cvCreateMat( 1, 1, CV_32FC1 );
    CvRandState rng;
    int code = -1;

    cvRandInit( &rng, 0, 1, -1, CV_RAND_UNI );

    cvZero( measurement );
    cvNamedWindow( "Kalman", 1 );

    for(;;)
    {
        cvRandSetRange( &rng, 0, 0.1, 0 );
        rng.disttype = CV_RAND_NORMAL;

        cvRand( &rng, state );

        memcpy( kalman->transition_matrix->data.fl, A, sizeof(A));   //A矩阵
        cvSetIdentity( kalman->measurement_matrix, cvRealScalar(1) );  //观测矩阵
        cvSetIdentity( kalman->process_noise_cov, cvRealScalar(1e-5) ); //
        cvSetIdentity( kalman->measurement_noise_cov, cvRealScalar(1e-1) );
        cvSetIdentity( kalman->error_cov_post, cvRealScalar(1));
        /* choose random initial state */
        cvRand( &rng, kalman->state_post );

        rng.disttype = CV_RAND_NORMAL;

        for(;;)
        {
            #define calc_point(angle)                                      \
                cvPoint( cvRound(img->width/2 + img->width/3*cos(angle)),  \
                         cvRound(img->height/2 - img->width/3*sin(angle)))

            float state_angle = state->data.fl[0];
	    CvPoint state_pt = calc_point(state_angle);

            /* predict point position */
            const CvMat* prediction = cvKalmanPredict( kalman, 0 );
            float predict_angle = prediction->data.fl[0];
            CvPoint predict_pt = calc_point(predict_angle);
            float measurement_angle;
            CvPoint measurement_pt;

            //rng的上下限[0，sqrt(kalman->measurement_noise_cov->data.fl[0]))
	    cvRandSetRange( &rng, 0, sqrt(kalman->measurement_noise_cov->data.fl[0]), 0 );
            cvRand( &rng, measurement );
//	    cvmSet(measurement, 0, 0, 3);
//	    cout<<cvmGet(measurement ,0 ,0)<<endl;
	    
            /* generate measurement */
            cvMatMulAdd( kalman->measurement_matrix, state, measurement, measurement );
//	    cout<<cvmGet(kalman->measurement_matrix, 0, 0)<<"  ";
//	    cout<<cvmGet(kalman->measurement_matrix, 0, 1)<<endl;
//	    cout<<cvmGet(kalman->measurement_matrix, 0, 2)<<"  ";
//	    cout<<cvmGet(kalman->measurement_matrix, 0, 3)<<"  ";
//	    cout<<cvmGet(kalman->measurement_matrix, 0, 4)<<"  ";
//	    cout<<cvmGet(kalman->measurement_matrix, 0, 5)<<endl;

            measurement_angle = measurement->data.fl[0];
            measurement_pt = calc_point(measurement_angle);

            /* plot points */
            #define draw_cross( center, color, d )                                 \
                cvLine( img, cvPoint( center.x - d, center.y - d ),                \
                             cvPoint( center.x + d, center.y + d ), color, 1, 0 ); \
                cvLine( img, cvPoint( center.x + d, center.y - d ),                \
                             cvPoint( center.x - d, center.y + d ), color, 1, 0 )

            cvZero( img );
            draw_cross( state_pt, CV_RGB(255,255,255), 3 );
            draw_cross( measurement_pt, CV_RGB(255,0,0), 3 );
            draw_cross( predict_pt, CV_RGB(0,255,0), 3 );
            cvLine( img, state_pt, predict_pt, CV_RGB(255,255,0), 3, 0 );

            /* adjust Kalman filter state */
            const CvMat* stt = cvKalmanCorrect( kalman, measurement );
//	    state = (CvMat*)stt;	

            cvRandSetRange( &rng, 0, sqrt(kalman->process_noise_cov->data.fl[0]), 0 );
            cvRand( &rng, process_noise );
            cvMatMulAdd( kalman->transition_matrix, state, process_noise, state );
	    cout<<cvmGet(state, 0, 0)<<"  ";
	    cout<<cvmGet(state, 1, 0)<<endl;

	    
            cvShowImage( "Kalman", img );
            code = cvWaitKey( 500 );
//
//            if( code > 0 ) /* break current simulation by pressing a key */
//                break;
        }
        if( code == 27 ) /* exit by ESCAPE */
            break;
    }

    return 0;
}