main.cpp

这是卡尔曼滤波算法用在数据融合中的程序实现

#ifndef OCCI_ORACLE
	#define WIN32COMMON
	#include "occi.h"
	using namespace oracle::occi;	
#endif
#include "occicontrol.h"

#include <vector>
using std::vector;
#pragma comment( lib, "oraocci9.lib" ) 
#pragma comment( lib, "oci.lib" )
#pragma comment( lib, "msvcrt.lib" ) 
#pragma comment( lib, "msvcprt.lib" ) 

#include <iostream.h>
#include "kalman_filter.h"


/*
typedef struct datasource
{
	float speed1;
	float speed2;
	float speed3;
}mydata;
*/
void main()
{
	
	matrix *Ai = new matrix(1, 1, new membuffer(100));
    matrix *Qi = new matrix(1, 1, new membuffer(100));
    matrix *Hi = new matrix(3, 1, new membuffer(100));
    matrix *Ri = new matrix(3, 3, new membuffer(100));
    matrix *x_initial = new matrix(1, 1, new membuffer(100));
	matrix *Pi = new matrix(1, 1, new membuffer(100));
	
    KalmanFilter *myKalman = new KalmanFilter(1, 3, *Ai,  *Hi, *Qi,*Ri, *x_initial, *Pi);
	myKalman->A.set(0,0.4);
	myKalman->Q.set(0,0.01);
	myKalman->H.set(0,0.4);
	myKalman->H.set(1,0.3);
	myKalman->H.set(2,0.3);
	myKalman->R.set(0,0,0.01);
	myKalman->R.set(1,1,0.01);
	myKalman->R.set(2,2,0.01);
	myKalman->R.set(0,1,0);
	myKalman->R.set(0,2,0);
	myKalman->R.set(1,0,0);
	myKalman->R.set(1,2,0);
	myKalman->R.set(2,0,0);
	myKalman->R.set(2,1,0);
	myKalman->P.set(0,0.01);
	myKalman->x.set(0,0);
	//cout<<" Matrix A is: "<<myKalman->A;
	//cout<<" Mtraix H is: "<<myKalman->H;
	//cout<<" Mtraix P is: "<<myKalman->P;
	//cout<<" Matrix Q is: "<<myKalman->Q;
	//cout<<" Matrix R is: "<<myKalman->R;

	
	Environment *env = Environment::createEnvironment(Environment::DEFAULT);
	//vector<struct datasource> vec;
    //mydata aa;
	try
	{
		Connection *conn = env->createConnection("rtfishz","rtfishz","ora9i");
		if (conn)
			cout << "SUCCESS - createConnection" << endl;
		else
			cout << "FAILURE - createConnection" << endl;
		
		Statement *stmt = conn->createStatement("select * from everyminutetest "); 
		ResultSet *rset = stmt->executeQuery();
		while (rset->next())
		{
		    myKalman->z.set(0,rset->getFloat(2));
		    myKalman->z.set(1,rset->getFloat(5));
		    myKalman->z.set(2,rset->getFloat(6));
	
	        //cout << " Matrix z is: " << myKalman->z;
	        //cout << " Matrix x is: " << myKalman->x;
	        //cout << " estimation of x is: " << myKalman->estimate();
	        cout << " prediction is: " << myKalman->next(myKalman->z) << endl;
			//cout << " the v1 is:" << rset->getFloat(2);
            //cout << " the v2 is:" << rset->getFloat(3);
	     	//cout << " the v3 is:" << rset->getFloat(4)<<endl;

		
		}
		cout<<endl;
		/*
		for(vector<struct datasource>::size_type it = 0; it < vec.size(); ++it)
		{
			struct datasource aa=vec[it];
			cout<<" vector speed1 is: "<<aa.speed1;
			cout<<" vector speed2 is: "<<aa.speed2;
			cout<<" vector speed3 is: "<<aa.speed3<<endl;

		    
		}
		*/
		stmt->closeResultSet (rset);
		conn->terminateStatement (stmt);
		env->terminateConnection (conn);
	}catch (SQLException ex){
		std::cout << ex.getMessage();}
}