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QKalmanFilter.cpp
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QKalmanFilter.cpp
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#include "QKalmanFilter.h"
QKalmanFilter::QKalmanFilter()
{
initVar();
}
QKalmanFilter::~QKalmanFilter(void)
{
}
void QKalmanFilter::initVar()
{
isInitPara = false;//The first epoch is only initialized once
m_VarChang = false;
m_KALMAN_MODEL = KALMAN_MODEL::PPP_STATIC;
m_KALMAN_SMOOTH_RANGE = KALMAN_SMOOTH_RANGE::NO_SMOOTH;
m_KALMAN_FILLTER = KALMAN_FILLTER::KALMAN_STANDARD;
m_SPP_Pos[0] = 0;m_SPP_Pos[1] = 0; m_SPP_Pos[2] = 0;
m_Xk_1.resize(32);// XiaoGongWei Update:2018.10.26
m_init_Xk.resize(32);// XiaoGongWei Update:2018.10.26
m_Xk_1.setZero();// XiaoGongWei Update:2018.10.26
m_init_Xk.setZero();// XiaoGongWei Update:2018.10.26
m_const_param = 4;// [dx,dy,dz,mf,clki]
m_sys_num = 1;
m_sys_str = "G";
m_LP_whight = 1e6;
m_xyz_dynamic_Qw = 1e6; m_zwd_Qw = 3e-8; m_clk_Qw = 1e6; m_amb_Qw = 1e-16; m_ion_Qw = 1e6;
m_xyz_dynamic_Pk = 1e6; m_zwd_Pk = 10; m_clk_Pk = 1e6; m_amb_Pk = 1e6; m_ion_Pk = 10;
}
void QKalmanFilter::setFilterParams(QVector<QStringList> Qw_Pk_LPacc)
{
if(Qw_Pk_LPacc.length() >= 2){
QStringList Qw_StrList = Qw_Pk_LPacc.at(0),Pk_StrList = Qw_Pk_LPacc.at(1);
if(Qw_StrList.length() < 5) return ; if(Pk_StrList.length() < 5) return ;
// set Qw
m_xyz_dynamic_Qw = Qw_StrList.at(0).toDouble(); m_zwd_Qw = Qw_StrList.at(1).toDouble();
m_clk_Qw = Qw_StrList.at(2).toDouble(); m_amb_Qw = Qw_StrList.at(3).toDouble();
m_ion_Qw = Qw_StrList.at(4).toDouble();
// set Pk
m_xyz_dynamic_Pk = Pk_StrList.at(0).toDouble(); m_zwd_Pk = Pk_StrList.at(1).toDouble();
m_clk_Pk= Pk_StrList.at(2).toDouble(); m_amb_Pk = Pk_StrList.at(3).toDouble();
m_ion_Pk = Pk_StrList.at(4).toDouble();
}
if(Qw_Pk_LPacc.length() >= 3){
QStringList LP_StrList = Qw_Pk_LPacc.at(2);
double LP_ratio = 1e3;
if(LP_StrList.length() == 2 && LP_StrList.at(0).toDouble() != 0 )
LP_ratio = LP_StrList.at(1).toDouble() / LP_StrList.at(0).toDouble();
m_LP_whight = LP_ratio * LP_ratio;// set m_LP_whight
}
}
// set KALMAN_MODEL
void QKalmanFilter::setModel(KALMAN_MODEL model_type)
{
m_KALMAN_MODEL = model_type;
m_sys_num = getSystemnum();
m_sys_str = getSatlitSys();
switch (model_type)
{
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_const_param = 3 + m_sys_num;//[dx,dy,dz,clki]
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_const_param = 4 + m_sys_num;//[dx,dy,dz,mf,clki]
break;
default:
m_const_param = 4+1;
break;
}
}
//Print matrix for Debug
void QKalmanFilter::printMatrix(MatrixXd mat)
{
qDebug()<<"Print Matrix......";
for (int i = 0; i < mat.rows();i++)
{
for (int j = 0;j< mat.cols();j++)
{
cout <<mat(i,j)<<",";
}
cout << endl;
}
cout<<"___________________";
}
//Initialize Kalman
void QKalmanFilter::initKalman(QVector< SatlitData > &currEpoch,MatrixXd &B,VectorXd &L)
{
int epochLenLB = currEpoch.length();
//Fk_1 initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Fk_1.resize(m_const_param, m_const_param);
m_Fk_1.setIdentity(m_const_param, m_const_param);
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_Fk_1.resize(m_const_param+epochLenLB,m_const_param+epochLenLB);
m_Fk_1.setIdentity(m_const_param+epochLenLB,m_const_param+epochLenLB);
break;
default:
break;
}
//Xk_1 pesodurange init Initialization, least squares initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Xk_1.resize(m_const_param);
m_Xk_1.setZero();
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_Xk_1.resize(epochLenLB+m_const_param);
m_Xk_1.setZero();
break;
default:
ErroTrace("QKalmanFilter::initKalman Bad.");
break;
}
m_Xk_1 = (B.transpose()*B).inverse()*B.transpose()*L;
m_init_Xk = m_Xk_1;
//Initialization state covariance matrix Pk_1 initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Pk_1.resize(m_const_param, m_const_param);
m_Pk_1.setZero();
m_Pk_1(0,0) = m_xyz_dynamic_Pk;m_Pk_1(1,1) = m_xyz_dynamic_Pk;m_Pk_1(2,2) = m_xyz_dynamic_Pk;
for(int i = 3; i < m_const_param;i++) m_Pk_1(i,i) = m_clk_Pk;// for clock
break;
case KALMAN_MODEL::PPP_STATIC:
case KALMAN_MODEL::PPP_KINEMATIC:
m_Pk_1.resize(m_const_param+epochLenLB,m_const_param+epochLenLB);
m_Pk_1.setZero();
m_Pk_1(0,0) = m_xyz_dynamic_Pk;m_Pk_1(1,1) = m_xyz_dynamic_Pk;m_Pk_1(2,2) = m_xyz_dynamic_Pk;
m_Pk_1(3,3) = m_zwd_Pk;
for(int i = 4; i < m_const_param;i++) m_Pk_1(i,i) = m_clk_Pk; // for clock
for (int i = 0;i < epochLenLB;i++) m_Pk_1(m_const_param+i,m_const_param+i) = m_amb_Pk;// for Ambiguity
break;
default:
ErroTrace("QKalmanFilter::initKalman Bad.");
break;
}
//Qk_1 system noise initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Qwk_1.resize(m_const_param, m_const_param);
m_Qwk_1.setZero();
for(int i = 3; i < m_const_param;i++) m_Qwk_1(i,i) = m_clk_Qw;// for clock
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_Qwk_1.resize(m_const_param+epochLenLB,m_const_param+epochLenLB);
m_Qwk_1.setZero();
m_Qwk_1(3,3) = m_zwd_Qw;//Zenith tropospheric residual variance
for(int i = 4; i < m_const_param;i++) m_Qwk_1(i,i) = m_clk_Qw; // for clock
break;
default:
ErroTrace("QKalmanFilter::initKalman Bad.");
break;
}
if(m_KALMAN_MODEL == KALMAN_MODEL::SPP_KINEMATIC || m_KALMAN_MODEL == KALMAN_MODEL::PPP_KINEMATIC)
{
m_Qwk_1(0,0) = m_xyz_dynamic_Qw;
m_Qwk_1(1,1) = m_xyz_dynamic_Qw;
m_Qwk_1(2,2) = m_xyz_dynamic_Qw;
}
//Rk_1 initialization is in place to determine that there is no change in the number of satellites
isInitPara = true;//No longer initialized after
}
//Initialize Kalman
void QKalmanFilter::initKalman_NoCombination(QVector< SatlitData > &currEpoch,MatrixXd &B,VectorXd &L)
{
int epochLenLB = currEpoch.length();
//Fk_1 initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Fk_1.resize(m_const_param+epochLenLB, m_const_param+epochLenLB);
m_Fk_1.setIdentity();
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_Fk_1.resize(m_const_param+3*epochLenLB,m_const_param+3*epochLenLB);
m_Fk_1.setIdentity();
break;
default:
break;
}
//Xk_1 pesodurange init Initialization, least squares initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Xk_1.resize(m_const_param+epochLenLB);
m_Xk_1.setZero();
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_Xk_1.resize(3*epochLenLB+m_const_param);
m_Xk_1.setZero();
break;
default:
ErroTrace("QKalmanFilter::initKalman Bad.");
break;
}
m_Xk_1 = (B.transpose()*B).inverse()*B.transpose()*L;
m_init_Xk = m_Xk_1;
//Initialization state covariance matrix Pk_1 initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Pk_1.resize(m_const_param+epochLenLB, m_const_param+epochLenLB);
m_Pk_1.setZero();
m_Pk_1(0,0) = m_xyz_dynamic_Pk;m_Pk_1(1,1) = m_xyz_dynamic_Pk;m_Pk_1(2,2) = m_xyz_dynamic_Pk;
for(int i = 3; i < m_const_param;i++) m_Pk_1(i,i) = m_clk_Pk;// for clock
for(int i = m_const_param; i < epochLenLB+m_const_param;i++) m_Pk_1(i,i) = m_ion_Pk;// for ION
break;
case KALMAN_MODEL::PPP_STATIC:
case KALMAN_MODEL::PPP_KINEMATIC:
m_Pk_1.resize(m_const_param+3*epochLenLB,m_const_param+3*epochLenLB);
m_Pk_1.setZero();
m_Pk_1(0,0) = m_xyz_dynamic_Pk;m_Pk_1(1,1) = m_xyz_dynamic_Pk;m_Pk_1(2,2) = m_xyz_dynamic_Pk;
m_Pk_1(3,3) = m_zwd_Pk;
for(int i = 4; i < m_const_param;i++) m_Pk_1(i,i) = m_clk_Pk; // for clock
for(int i = m_const_param; i < m_const_param+epochLenLB;i++) m_Pk_1(i,i) = m_ion_Pk; // for ION
for (int i = m_const_param+epochLenLB;i < m_const_param+3*epochLenLB;i++) m_Pk_1(i,i) = m_amb_Pk;// for Ambiguity
break;
default:
ErroTrace("QKalmanFilter::initKalman Bad.");
break;
}
//Qk_1 system noise initialization
switch (m_KALMAN_MODEL) {
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
m_Qwk_1.resize(m_const_param+epochLenLB, m_const_param+epochLenLB);
m_Qwk_1.setZero();
for(int i = 3; i < m_const_param;i++) m_Qwk_1(i,i) = m_clk_Qw;// for clock
for(int i = m_const_param; i < epochLenLB+m_const_param;i++) m_Pk_1(i,i) = m_ion_Qw;// for ION
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
m_Qwk_1.resize(m_const_param+3*epochLenLB,m_const_param+3*epochLenLB);
m_Qwk_1.setZero();
m_Qwk_1(3,3) = m_zwd_Qw;//Zenith tropospheric residual variance
for(int i = 4; i < m_const_param;i++) m_Qwk_1(i,i) = m_clk_Qw; // for clock
for(int i = m_const_param; i < m_const_param+epochLenLB;i++) m_Qwk_1(i,i) = m_ion_Qw; // for ION
break;
default:
ErroTrace("QKalmanFilter::initKalman Bad.");
break;
}
if(m_KALMAN_MODEL == KALMAN_MODEL::SPP_KINEMATIC || m_KALMAN_MODEL == KALMAN_MODEL::PPP_KINEMATIC)
{
m_Qwk_1(0,0) = m_xyz_dynamic_Qw;
m_Qwk_1(1,1) = m_xyz_dynamic_Qw;
m_Qwk_1(2,2) = m_xyz_dynamic_Qw;
}
//Rk_1 initialization is in place to determine that there is no change in the number of satellites
isInitPara = true;//No longer initialized after
}
//Change the Kalman parameter size (only PPP can change paramater)
void QKalmanFilter::changeKalmanPara( QVector< SatlitData > &epochSatlitData,QVector< int >oldPrnFlag )
{
int epochLenLB = epochSatlitData.length();
m_Fk_1.resize(m_const_param+epochLenLB,m_const_param+epochLenLB);
m_Fk_1.setZero();
m_Fk_1.setIdentity(m_const_param+epochLenLB,m_const_param+epochLenLB);
//Fk_1(4,4) = 0;//Static PPP has only a clock difference of 0
//Xk_1 change
VectorXd tempXk_1 = m_Xk_1;
m_Xk_1.resize(epochLenLB+m_const_param);
m_Xk_1.setZero();
//Xk.resize(epochLenLB+5);
for (int i = 0;i < m_const_param;i++)
m_Xk_1(i) = tempXk_1(i);
for (int i = 0;i<epochLenLB;i++)
{
if (oldPrnFlag.at(i)!=-1)//Save the old satellite ambiguity
m_Xk_1(m_const_param+i) = tempXk_1(oldPrnFlag.at(i)+m_const_param);
else
{//New satellite ambiguity calculation
SatlitData oneStalit = epochSatlitData.at(i);
m_Xk_1(m_const_param+i) = (oneStalit.PP3 - oneStalit.LL3)/M_GetLamta3(oneStalit.Frq[0],oneStalit.Frq[1]);
}
}
//Qk_1 system noise will not be updated, system noise is not measurable
m_Qwk_1.resize(m_const_param+epochLenLB,m_const_param+epochLenLB);
m_Qwk_1.setZero();
if(m_KALMAN_MODEL == KALMAN_MODEL::PPP_KINEMATIC)
{
m_Qwk_1(0,0) = m_xyz_dynamic_Qw;
m_Qwk_1(1,1) = m_xyz_dynamic_Qw;
m_Qwk_1(2,2) = m_xyz_dynamic_Qw;
}
m_Qwk_1(3,3) = m_zwd_Qw;//Zenith tropospheric residual variance
for(int i = 4; i < m_const_param;i++) m_Qwk_1(i,i) = m_clk_Qw; // for clock
//Reset Rk_1 observation noise matrix (reset on the outside, no need to repeat reset here)
//The saved state covariance matrix Pk_1 is increased or decreased (here is more complicated, the main idea is to take out old satellite data, and initialize the new satellite data)
MatrixXd tempPk_1 = m_Pk_1;
m_Pk_1.resize(m_const_param+epochLenLB, m_const_param+epochLenLB);
m_Pk_1.setZero();
//If the number of satellites changes
for (int i = 0;i < m_const_param;i++)
for (int j = 0;j < m_const_param;j++)
m_Pk_1(i,j) = tempPk_1(i,j);
for (int n = 0; n < epochLenLB;n++)
{
int flag = oldPrnFlag.at(n);
if ( flag != -1)//Description: The previous epoch contains this satellite data and needs to be taken from tempPk_1
{
flag+=m_const_param;//The number of rows of this satellite in the original data tempPk_1
for (int i = 0;i < tempPk_1.cols();i++)
{//Take out from tempPk_1 and skip the data with oldPrnFlag -1
if (i < m_const_param)
{
m_Pk_1(n+m_const_param,i) = tempPk_1(flag,i);
m_Pk_1(i,n+m_const_param) = tempPk_1(i,flag);
}
else
{
int findCols = i - m_const_param,saveFlag = -1;
//Find if the data exists in the old linked list and where it will be saved
for (int m = 0;m < oldPrnFlag.length();m++)
{
if (findCols == oldPrnFlag.at(m))
{
saveFlag = m;
break;
}
}
if (saveFlag!=-1)
{
m_Pk_1(n+m_const_param,saveFlag+m_const_param) = tempPk_1(flag,i);
//Pk_1(saveFlag+5,n+5) = tempPk_1(i,flag);
}
}//if (i < 5)
}//for (int i = 0;i < tempPk_1.cols();i++)
}
else
{
m_Pk_1(n+m_const_param,n+m_const_param) = m_amb_Pk;
// for (int i = 0;i < m_const_param;i++)
// {
// m_Pk_1(n+m_const_param,i) = 1;
// m_Pk_1(i,n+m_const_param) = 1;
// }
}
}//Pk_1 saves the data
m_VarChang = true;
}
//Change the Kalman parameter size (only PPP can change paramater)
void QKalmanFilter::changeKalmanPara_NoCombination( QVector< SatlitData > &epochSatlitData,QVector< int >oldPrnFlag, int preEpochLen)
{
int epochLenLB = epochSatlitData.length();
m_Fk_1.resize(m_const_param+3*epochLenLB,m_const_param+3*epochLenLB);
m_Fk_1.setZero();
m_Fk_1.setIdentity();
//Fk_1(4,4) = 0;//Static PPP has only a clock difference of 0
//Xk_1 change
VectorXd tempXk_1 = m_Xk_1;
m_Xk_1.resize(3*epochLenLB+m_const_param);
m_Xk_1.setZero();
for (int i = 0;i < m_const_param;i++)
m_Xk_1(i) = tempXk_1(i);
for (int i = 0;i<epochLenLB;i++)
{
if (oldPrnFlag.at(i)!=-1)//Save the old satellite ION and L1 L2 ambiguity
{
m_Xk_1(m_const_param+i) = tempXk_1(oldPrnFlag.at(i)+m_const_param);// for ION
m_Xk_1(m_const_param+epochLenLB+i) = tempXk_1(oldPrnFlag.at(i)+preEpochLen+m_const_param);// for L1 ambiguity
m_Xk_1(m_const_param+2*epochLenLB+i) = tempXk_1(oldPrnFlag.at(i)+2*preEpochLen+m_const_param);// for L1 ambiguity
}
else
{//New satellite ambiguity calculation
SatlitData oneStalit = epochSatlitData.at(i);
m_Xk_1(m_const_param+epochLenLB+i) = (oneStalit.C1 - oneStalit.L1)/oneStalit.Frq[0];// new L1 ambiguity
m_Xk_1(m_const_param+2*epochLenLB+i) = (oneStalit.C2 - oneStalit.L2)/oneStalit.Frq[1];// new L2 ambiguity
}
}
// m_matrix.writeCSV("newXk.csv", m_Xk_1);
// m_matrix.writeCSV("oldXk.csv", tempXk_1);
//Qk_1 system noise will not be updated, system noise is not measurable
m_Qwk_1.resize(m_const_param+3*epochLenLB,m_const_param+3*epochLenLB);
m_Qwk_1.setZero();
if(m_KALMAN_MODEL == KALMAN_MODEL::PPP_KINEMATIC)
{
m_Qwk_1(0,0) = m_xyz_dynamic_Qw;
m_Qwk_1(1,1) = m_xyz_dynamic_Qw;
m_Qwk_1(2,2) = m_xyz_dynamic_Qw;
}
m_Qwk_1(3,3) = m_zwd_Qw;//Zenith tropospheric residual variance
for(int i = 4; i < m_const_param;i++) m_Qwk_1(i,i) = m_clk_Qw; // for clock
for(int i = m_const_param; i < m_const_param+epochLenLB;i++) m_Qwk_1(i,i) = m_ion_Qw; // for ION
//Reset Rk_1 observation noise matrix (reset on the outside, no need to repeat reset here)
//The saved state covariance matrix Pk_1 is increased or decreased (here is more complicated, the main idea is to take out old satellite data, and initialize the new satellite data)
MatrixXd tempPk_1 = m_Pk_1;
m_Pk_1.resize(m_const_param+3*epochLenLB, m_const_param+3*epochLenLB);
m_Pk_1.setZero();
//If the number of satellites changes
for (int i = 0;i < m_const_param;i++)
for (int j = 0;j < m_const_param;j++)
m_Pk_1(i,j) = tempPk_1(i,j);
for (int n = 0; n < epochLenLB;n++)
{
int flag = oldPrnFlag.at(n);
if ( flag != -1)//Description: The previous epoch contains this satellite data and needs to be taken from tempPk_1
{
flag+=m_const_param;//The number of rows of this satellite in the original data tempPk_1
for (int i = 0;i < tempPk_1.cols();i++)
{//Take out from tempPk_1 and skip the data with oldPrnFlag -1
if (i < m_const_param)
{
// for ION
m_Pk_1(n+m_const_param,i) = tempPk_1(flag,i);
m_Pk_1(i,n+m_const_param) = tempPk_1(i,flag);
// for L1 AMB
m_Pk_1(n+m_const_param+epochLenLB,i) = tempPk_1(flag+preEpochLen,i);
m_Pk_1(i,n+m_const_param+epochLenLB) = tempPk_1(i,flag+preEpochLen);
// for L2 AMB
m_Pk_1(n+m_const_param+2*epochLenLB,i) = tempPk_1(flag+2*preEpochLen,i);
m_Pk_1(i,n+m_const_param+2*epochLenLB) = tempPk_1(i,flag+2*preEpochLen);
}
else
{
int findCols = i - m_const_param,saveFlag = -1;
//Find if the data exists in the old linked list and where it will be saved
for (int m = 0;m < oldPrnFlag.length();m++)
{
if (findCols == oldPrnFlag.at(m))
{
saveFlag = m;
break;
}
}
if (saveFlag!=-1)
{
// qDebug() <<"(" << flag << "," << i << ") -> " <<" (" << n+m_const_param << "," << saveFlag+m_const_param << ")";
m_Pk_1(n+m_const_param,saveFlag+m_const_param) = tempPk_1(flag,i);// for ION
m_Pk_1(n+m_const_param,saveFlag+m_const_param+epochLenLB) = tempPk_1(flag,i+preEpochLen);
m_Pk_1(n+m_const_param,saveFlag+m_const_param+2*epochLenLB) = tempPk_1(flag,i+2*preEpochLen);
m_Pk_1(n+m_const_param+epochLenLB,saveFlag+m_const_param) = tempPk_1(flag+preEpochLen,i);// for L1 AMB
m_Pk_1(n+m_const_param+epochLenLB,saveFlag+m_const_param+epochLenLB) = tempPk_1(flag+preEpochLen,i+preEpochLen);// for L1 AMB
m_Pk_1(n+m_const_param+epochLenLB,saveFlag+m_const_param+2*epochLenLB) = tempPk_1(flag+preEpochLen,i+2*preEpochLen);// for L1 AMB
m_Pk_1(n+m_const_param+2*epochLenLB,saveFlag+m_const_param) = tempPk_1(flag+2*preEpochLen,i);// for L2 AMB
m_Pk_1(n+m_const_param+2*epochLenLB,saveFlag+m_const_param+epochLenLB) = tempPk_1(flag+2*preEpochLen,i+preEpochLen);// for L2 AMB
m_Pk_1(n+m_const_param+2*epochLenLB,saveFlag+m_const_param+2*epochLenLB) = tempPk_1(flag+2*preEpochLen,i+2*preEpochLen);// for L2 AMB
}
}//if (i < 5)
}//for (int i = 0;i < tempPk_1.cols();i++)
}
else
{
m_Pk_1(n+m_const_param,n+m_const_param) = m_ion_Pk;// for ION
m_Pk_1(n+m_const_param+epochLenLB,n+m_const_param+epochLenLB) = m_amb_Pk;// for L1 amb
m_Pk_1(n+m_const_param+2*epochLenLB,n+m_const_param+2*epochLenLB) = m_amb_Pk;// for L2 amb
}
}//Pk_1 saves the data
// m_matrix.writeCSV("newPk.csv", m_Pk_1);
// m_matrix.writeCSV("oldPk.csv", tempPk_1);
m_VarChang = true;
}
//First Kalman version Mr. Jikun Ou
// PBk is Weight matrix
void QKalmanFilter::KalmanforStaticOu(MatrixXd Bk,VectorXd Lk,MatrixXd F,MatrixXd Qwk,MatrixXd PBk,VectorXd &tXk_1,MatrixXd &tPk_1)
{
}
//Third version use to change Kalman
void QKalmanFilter::KalmanforStatic(MatrixXd Bk,VectorXd Lk,MatrixXd F,MatrixXd Qwk,
MatrixXd Rk,VectorXd &tXk_1,MatrixXd &tPk_1)
{
//Time update
VectorXd Xkk_1 = F*tXk_1,Vk;
MatrixXd Pkk_1 = F*tPk_1*F.transpose() + Qwk,I,tempKB,Kk;
//Calculated gain matrix
Kk = (Pkk_1*Bk.transpose())*((Bk*Pkk_1*Bk.transpose() + Rk).inverse());
//Filter update
Vk = Lk - Bk*Xkk_1;
//Update X
tXk_1 = Xkk_1 + Kk*Vk;
//Filtered residual, normal download wave is very small
VectorXd Vk_temp = Lk - Bk*tXk_1;
tempKB = Kk*Bk;
I.resize(tempKB.rows(),tempKB.cols());
I.setIdentity();
//Update P (Case I) (this update is extremely unstable)
tPk_1 = (I - tempKB)*Pkk_1;
// m_matrix.writeCSV("B.csv", Bk);
// m_matrix.writeCSV("L.csv", Lk);
//Update P(Case II)
// MatrixXd Mk_1 = Pkk_1.inverse() + Bk.transpose()*Rk.inverse()*Bk;
// tPk_1 =Mk_1.inverse();
// MatrixXd newPk = 0.5*(tPk_1 + tPk_1.transpose());
// tPk_1 = newPk;
//printMatrix(tPk_1);
// tPk_1 = 0.5*(tPk_1 + tPk_1.transpose()); //(In theory, it should be added but added or beating. Changed the original covariance data)
//printMatrix(tPk_1);
}
////Third version use to change Kalman
//void QKalmanFilter::KalmanforStatic(MatrixXd Bk,VectorXd Lk,MatrixXd F,MatrixXd Qwk,
// MatrixXd Rk,VectorXd &tXk_1,MatrixXd &tPk_1)
//{
// //
//// int keepnum = -1;
// int keepnum = 9;
// m_matrix.keepMatPricision(Bk,keepnum);
// m_matrix.keepMatPricision(Lk,keepnum);
// m_matrix.keepMatPricision(F,keepnum);
// m_matrix.keepMatPricision(Qwk,keepnum);
// m_matrix.keepMatPricision(Rk,keepnum);
// m_matrix.keepMatPricision(tXk_1,keepnum);
// m_matrix.keepMatPricision(tPk_1,keepnum);
// //Time update
// VectorXd Xkk_1 = F*tXk_1,Vk;
// MatrixXd Pkk_1 = F*tPk_1*F.transpose() + Qwk,I,tempKB,Kk;
// m_matrix.keepMatPricision(Xkk_1,keepnum);
// m_matrix.keepMatPricision(Pkk_1,keepnum);
// //Calculated gain matrix
// Kk = (Pkk_1*Bk.transpose())*((Bk*Pkk_1*Bk.transpose() + Rk).inverse());
// m_matrix.keepMatPricision(Kk,keepnum);
// //Filter update
// Vk = Lk - Bk*Xkk_1;
// m_matrix.keepMatPricision(Vk,keepnum);
// //Update X
// tXk_1 = Xkk_1 + Kk*Vk;
// m_matrix.keepMatPricision(tXk_1,keepnum);
// //Filtered residual, normal download wave is very small
// VectorXd Vk_temp = Lk - Bk*tXk_1;
// tempKB = Kk*Bk;
// I.resize(tempKB.rows(),tempKB.cols());
// I.setIdentity();
// m_matrix.keepMatPricision(tempKB,keepnum);
// //Update P (Case I) (this update is extremely unstable)
// tPk_1 = (I - tempKB)*Pkk_1;
// //Update P(Case II)
//// MatrixXd Mk_1 = Pkk_1.inverse() + Bk.transpose()*Rk.inverse()*Bk;
//// tPk_1 =Mk_1.inverse();
// //printMatrix(tPk_1);
// m_matrix.keepMatPricision(tPk_1,keepnum);
//// tPk_1 = 0.5*(tPk_1 + tPk_1.transpose()); //(In theory, it should be added but added or beating. Changed the original covariance data)
// //printMatrix(tPk_1);
//}
// get matrix B and observer L for Combination
void QKalmanFilter::Obtaining_equation(QVector< SatlitData > &currEpoch, double *m_ApproxRecPos, MatrixXd &mat_B, VectorXd &Vct_L,
MatrixXd &mat_P)
{
int epochLenLB = currEpoch.length(), const_num = 3;
MatrixXd B, P;
VectorXd L, sys_len;
sys_len.resize(m_sys_str.length());
sys_len.setZero();
switch(m_KALMAN_MODEL)
{
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
B.resize(epochLenLB,m_const_param);
P.resize(epochLenLB,epochLenLB);
L.resize(epochLenLB);
const_num = 3;// 3 is conntain [dx,dy,dz]
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
B.resize(2*epochLenLB,epochLenLB+m_const_param);
P.resize(2*epochLenLB,2*epochLenLB);
L.resize(2*epochLenLB);
const_num = 4;// 4 is conntain [dx,dy,dz,mf]
break;
default:
ErroTrace("QKalmanFilter::Obtaining_equation you should use setModel().");
break;
}
// init matrix
B.setZero();
L.setZero();
P.setIdentity();
bool is_find_base_sat = false;
for (int i = 0; i < epochLenLB;i++)
{
SatlitData oneSatlit = currEpoch.at(i);
double li = 0,mi = 0,ni = 0,p0 = 0,dltaX = 0,dltaY = 0,dltaZ = 0;
dltaX = oneSatlit.X - m_ApproxRecPos[0];
dltaY = oneSatlit.Y - m_ApproxRecPos[1];
dltaZ = oneSatlit.Z - m_ApproxRecPos[2];
p0 = qSqrt(dltaX*dltaX+dltaY*dltaY+dltaZ*dltaZ);
// compute li mi ni
li = dltaX/p0;mi = dltaY/p0;ni = dltaZ/p0;
//Correction of each
double dlta = 0;
dlta = - oneSatlit.StaClock + oneSatlit.SatTrop - oneSatlit.Relativty -
oneSatlit.Sagnac - oneSatlit.TideEffect - oneSatlit.AntHeight;
// set B L P
double LP_whight = m_LP_whight;
switch(m_KALMAN_MODEL)
{
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
//Computational B matrix
//L3 carrier matrix
B(i,0) = li;B(i,1) = mi;B(i,2) = ni;B(i,3) = -1;
// debug by xiaogongwei 2019.04.03 for ISB
for(int k = 1; k < m_sys_str.length();k++)
{
if(m_sys_str[k] == oneSatlit.SatType)
{
B(i,3+k) = -1;
sys_len[k] = 1;//good no zeros cloumn in B,sys_lenmybe 0 1 1 0(debug by xiaogongwei 2019.04.09 for ISB)
}
}
// debug by xiaogongwei 2019.04.10 is exist base system satlite clk
if(m_sys_str[0] == oneSatlit.SatType)
is_find_base_sat = true;
//Pseudorange code L
if(KALMAN_SMOOTH_RANGE::SMOOTH == m_KALMAN_SMOOTH_RANGE)
{
L(i) = p0 - oneSatlit.PP3_Smooth + dlta;
// Computing weight matrix PP3
P(i, i) = 1 / oneSatlit.PP3_Smooth_Q;// Pseudo-range right
}
else
{
L(i) = p0 - oneSatlit.PP3 + dlta;
// Computing weight matrix P
P(i, i) = oneSatlit.SatWight;// Pseudo-range right
}
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
//Computational B matrix
//L3 carrier matrix
B(i,0) = li;B(i,1) = mi;B(i,2) = ni;B(i,3) = -oneSatlit.StaTropMap;B(i,4) = -1;
for (int n = 0;n < epochLenLB;n++)//The diagonal part of the rear part initializes the wavelength of Lamta3, and the rest is 0.
if (i == n)
B(i,m_const_param+n) = M_GetLamta3(oneSatlit.Frq[0],oneSatlit.Frq[1]);//LL3 wavelength
//P3 pseudorange code matrix
B(i+epochLenLB,0) = li;B(i+epochLenLB,1) = mi;B(i+epochLenLB,2) = ni;B(i+epochLenLB,3) = -oneSatlit.StaTropMap;B(i+epochLenLB,4) = -1;
// debug by xiaogongwei 2019.04.03 for ISB
for(int k = 1; k < m_sys_str.length();k++)
{
if(m_sys_str[k] == oneSatlit.SatType)
{
B(i,4+k) = -1;
B(i+epochLenLB,4+k) = -1;
sys_len[k] = 1;//good no zeros cloumn in B,sys_lenmybe 0 1 1 0(debug by xiaogongwei 2019.04.09 for ISB)
}
}
// debug by xiaogongwei 2019.04.10 is exist base system satlite clk
if(m_sys_str[0] == oneSatlit.SatType)
is_find_base_sat = true;
//Carrier L pseudorange code L
L(i) = p0 - oneSatlit.LL3 + dlta;
L(i+epochLenLB) = p0 - oneSatlit.PP3 + dlta;
// Computing weight matrix P
// if(oneSatlit.UTCTime.epochNum <= 100) LP_whight = 1e6;// for convergence
P(i, i) = oneSatlit.SatWight * LP_whight;// Carrier weight
P(i + epochLenLB, i + epochLenLB) = oneSatlit.SatWight;// Pseudo-range right
break;
default:
ErroTrace("QKalmanFilter::Obtaining_equation you should use setModel().");
break;
}//switch(m_KALMAN_MODEL)
}//B, L is calculated
// save data to mat_B
mat_B = B;
Vct_L = L;
mat_P = P;
// m_matrix.writeCSV("./csv/mat_B.csv", mat_B);
// m_matrix.writeCSV("./csv/mat_P.csv", mat_P);
// debug by xiaogongwei 2019.04.04
int no_zero = sys_len.size() - 1 - sys_len.sum();
if(no_zero > 0 || !is_find_base_sat)
{
int new_hang = B.rows() + no_zero, new_lie = B.cols(), flag = 0;
if(!is_find_base_sat) new_hang++; // debug by xiaogongwei 2019.04.10 is exist base system satlite clk
mat_B.resize(new_hang,new_lie);
mat_P.resize(new_hang,new_hang);
Vct_L.resize(new_hang);
mat_B.setZero();
Vct_L.setZero();
mat_P.setIdentity();
// debug by xiaogongwei 2019.04.10 is exist base system satlite clk
if(!is_find_base_sat)
{
for(int i = 0;i < B.rows();i++)
B(i, const_num) = 0;
mat_B(mat_B.rows() - 1, const_num) = 1;
}
mat_B.block(0,0,B.rows(),B.cols()) = B;
mat_P.block(0,0,P.rows(),P.cols()) = P;
Vct_L.head(L.rows()) = L;
for(int i = 1; i < sys_len.size();i++)
{
if(0 == sys_len[i])
{
mat_B(B.rows()+flag, const_num+i) = 1;
flag++;
}
}
}//if(no_zero > 0)
// m_matrix.writeCSV("./csv/mat_B1.csv", mat_B);
// m_matrix.writeCSV("./csv/mat_P1.csv", mat_P);
}
// get matrix B and observer L for No Combination
void QKalmanFilter::Obtaining_equation_NoCombination(QVector< SatlitData > &currEpoch, double *m_ApproxRecPos, MatrixXd &mat_B, VectorXd &Vct_L,
MatrixXd &mat_P)
{
int epochLenLB = currEpoch.length(), const_num = 3;
MatrixXd B, P;
VectorXd L, sys_len;
sys_len.resize(m_sys_str.length());
sys_len.setZero();
switch(m_KALMAN_MODEL)
{
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
B.resize(2*epochLenLB,m_const_param+epochLenLB);
P.resize(2*epochLenLB,2*epochLenLB);
L.resize(2*epochLenLB);
const_num = 3;// 3 is conntain [dx,dy,dz]
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
B.resize(4*epochLenLB,3*epochLenLB+m_const_param);
P.resize(4*epochLenLB,4*epochLenLB);
L.resize(4*epochLenLB);
const_num = 4;// 4 is conntain [dx,dy,dz,mf]
break;
default:
ErroTrace("QKalmanFilter::Obtaining_equation you should use setModel().");
break;
}
// init matrix
B.setZero();
L.setZero();
P.setIdentity();
bool is_find_base_sat = false;
for (int i = 0; i < epochLenLB;i++)
{
SatlitData oneSatlit = currEpoch.at(i);
double li = 0,mi = 0,ni = 0,p0 = 0,dltaX = 0,dltaY = 0,dltaZ = 0;
dltaX = oneSatlit.X - m_ApproxRecPos[0];
dltaY = oneSatlit.Y - m_ApproxRecPos[1];
dltaZ = oneSatlit.Z - m_ApproxRecPos[2];
p0 = qSqrt(dltaX*dltaX+dltaY*dltaY+dltaZ*dltaZ);
// compute li mi ni
li = dltaX/p0;mi = dltaY/p0;ni = dltaZ/p0;
//Correction of each
double dlta = 0;
dlta = - oneSatlit.StaClock + oneSatlit.SatTrop - oneSatlit.Relativty -
oneSatlit.Sagnac - oneSatlit.TideEffect - oneSatlit.AntHeight;
// set B L P
double LP_whight = m_LP_whight;
double F1 = oneSatlit.Frq[0], F2 = oneSatlit.Frq[1];
double lamda1 = M_C/F1, lamda2 = M_C/F2;
switch(m_KALMAN_MODEL)
{
case KALMAN_MODEL::SPP_STATIC:
case KALMAN_MODEL::SPP_KINEMATIC:
//Computational B matrix
//L3 carrier matrix
B(2*i,0) = li;B(2*i,1) = mi;B(2*i,2) = ni;B(2*i,3) = -1;
B(2*i+1,0) = li;B(2*i+1,1) = mi;B(2*i+1,2) = ni;B(2*i+1,3) = -1;
B(2*i,i+m_const_param) = -1;// ION for P1
B(2*i+1,i+m_const_param) = -(F1*F1)/(F2*F2);// ION for P2
// debug by xiaogongwei 2019.04.03 for ISB
for(int k = 1; k < m_sys_str.length();k++)
{
if(m_sys_str[k] == oneSatlit.SatType)
{
B(2*i,3+k) = -1;
B(2*i+1,3+k) = -1;
sys_len[k] = 1;//good no zeros cloumn in B,sys_lenmybe 0 1 1 0(debug by xiaogongwei 2019.04.09 for ISB)
}
}
// debug by xiaogongwei 2019.04.10 is exist base system satlite clk
if(m_sys_str[0] == oneSatlit.SatType)
is_find_base_sat = true;
//Pseudorange code not use KALMAN_SMOOTH_RANGE::SMOOTH
//Pseudorange code L
if(KALMAN_SMOOTH_RANGE::SMOOTH == m_KALMAN_SMOOTH_RANGE)
{
L(2*i) = p0 - oneSatlit.CC1_Smooth + dlta;
L(2*i+1) = p0 - oneSatlit.CC2_Smooth + dlta;
P(2*i, 2*i) = 1 / oneSatlit.CC1_Smooth_Q;// Pseudo-range Wight
P(2*i+1, 2*i+1) = 1 / oneSatlit.CC2_Smooth_Q;// Pseudo-range Wight
}
else
{
L(2*i) = p0 - oneSatlit.C1 + dlta;
L(2*i+1) = p0 - oneSatlit.C2 + dlta;
P(2*i, 2*i) = oneSatlit.SatWight;
P(2*i+1, 2*i+1) = oneSatlit.SatWight;
}
break;
case KALMAN_MODEL::PPP_KINEMATIC:
case KALMAN_MODEL::PPP_STATIC:
//Computational B matrix
//L carrier matrix
B(2*i,0) = li;B(2*i,1) = mi;B(2*i,2) = ni;B(2*i,3) = -oneSatlit.StaTropMap;B(2*i,4) = -1; // L1
B(2*i+1,0) = li;B(2*i+1,1) = mi;B(2*i+1,2) = ni;B(2*i+1,3) = -oneSatlit.StaTropMap;B(2*i+1,4) = -1; // L2
B(2*i,i+m_const_param) = +1;// ION for L1
B(2*i+1,i+m_const_param) = +(F1*F1)/(F2*F2);// ION for L2
B(2*i,i+m_const_param+epochLenLB) = lamda1;// N1 for L1
B(2*i+1,i+m_const_param+2*epochLenLB) = lamda2;// N2 for L2
//P pseudorange code matrix
B(2*i+2*epochLenLB,0) = li;B(2*i+2*epochLenLB,1) = mi;B(2*i+2*epochLenLB,2) = ni;B(2*i+2*epochLenLB,3) = -oneSatlit.StaTropMap;B(2*i+2*epochLenLB,4) = -1;
B(2*i+2*epochLenLB+1,0) = li;B(2*i+2*epochLenLB+1,1) = mi;B(2*i+2*epochLenLB+1,2) = ni;B(2*i+2*epochLenLB+1,3) = -oneSatlit.StaTropMap;B(2*i+2*epochLenLB+1,4) = -1;
B(2*i+2*epochLenLB,i+m_const_param) = -1;// ION for P1
B(2*i+2*epochLenLB+1,i+m_const_param) = -(F1*F1)/(F2*F2);// ION for P2
// debug by xiaogongwei 2019.04.03 for ISB
for(int k = 1; k < m_sys_str.length();k++)
{
if(m_sys_str[k] == oneSatlit.SatType)
{
B(2*i,const_num+k) = -1;
B(2*i+1,const_num+k) = -1;
B(2*i+2*epochLenLB,const_num+k) = -1;
B(2*i+2*epochLenLB+1,const_num+k) = -1;
sys_len[k] = 1;//good no zeros cloumn in B,sys_lenmybe 0 1 1 0(debug by xiaogongwei 2019.04.09 for ISB)
}
}
// debug by xiaogongwei 2019.04.10 is exist base system satlite clk
if(m_sys_str[0] == oneSatlit.SatType)
is_find_base_sat = true;
//Carrier L pseudorange code L
L(2*i) = p0 - oneSatlit.LL1 + dlta;
L(2*i+1) = p0 - oneSatlit.LL2 + dlta;
L(2*i+2*epochLenLB) = p0 - oneSatlit.CC1 + dlta;
L(2*i+2*epochLenLB+1) = p0 - oneSatlit.CC2 + dlta;
// Computing weight matrix P
P(2*i, 2*i) = oneSatlit.SatWight * LP_whight;// Carrier L1 weight
P(2*i+1, 2*i+1) = oneSatlit.SatWight * LP_whight;// Carrier L2 weight
P(2*i + epochLenLB, 2*i + epochLenLB) = oneSatlit.SatWight;// Pseudo-range C1 weight
P(2*i + epochLenLB+1, 2*i + epochLenLB+1) = oneSatlit.SatWight;// Pseudo-range C2 weight
break;
default:
ErroTrace("QKalmanFilter::Obtaining_equation you should use setModel().");
break;
}//switch(m_KALMAN_MODEL)
}//B, L is calculated
// save data to mat_B
mat_B = B;
Vct_L = L;
mat_P = P;
// m_matrix.writeCSV("./csv/mat_B.csv", mat_B);
// m_matrix.writeCSV("./csv/mat_P.csv", mat_P);
// debug by xiaogongwei 2019.04.04
int no_zero = sys_len.size() - 1 - sys_len.sum();
if(no_zero > 0 || !is_find_base_sat)
{
int new_hang = B.rows() + no_zero, new_lie = B.cols(), flag = 0;
if(!is_find_base_sat) new_hang++; // debug by xiaogongwei 2019.04.10 is exist base system satlite clk
mat_B.resize(new_hang,new_lie);
mat_P.resize(new_hang,new_hang);
Vct_L.resize(new_hang);
mat_B.setZero();
Vct_L.setZero();
mat_P.setIdentity();
// debug by xiaogongwei 2019.04.10 is exist base system satlite clk
if(!is_find_base_sat)
{
for(int i = 0;i < B.rows();i++)
B(i, const_num) = 0;
mat_B(mat_B.rows() - 1, const_num) = 1;
}
mat_B.block(0,0,B.rows(),B.cols()) = B;
mat_P.block(0,0,P.rows(),P.cols()) = P;
Vct_L.head(L.rows()) = L;
for(int i = 1; i < sys_len.size();i++)
{
if(0 == sys_len[i])
{
mat_B(B.rows()+flag, const_num+i) = 1;
flag++;
}
}
}//if(no_zero > 0)
// m_matrix.writeCSV("./csv/mat_B1.csv", mat_B);
// m_matrix.writeCSV("./csv/mat_P1.csv", mat_P);
}
//Second version
bool QKalmanFilter::KalmanforStatic(QVector< SatlitData > &preEpoch,QVector< SatlitData > &currEpoch,double *m_ApproxRecPos,
VectorXd &X,MatrixXd &P)
{
if (!isInitPara)
{
m_SPP_Pos[0] = m_ApproxRecPos[0];
m_SPP_Pos[1] = m_ApproxRecPos[1];
m_SPP_Pos[2] = m_ApproxRecPos[2];
}
//judge is Kinematic
if(m_KALMAN_MODEL == KALMAN_MODEL::PPP_KINEMATIC || m_KALMAN_MODEL == KALMAN_MODEL::SPP_KINEMATIC)
{
// we solver five parameter[dx,dy,dz,dTrop,dClock],so epochLenLB > 4
m_SPP_Pos[0] = m_ApproxRecPos[0];
m_SPP_Pos[1] = m_ApproxRecPos[1];
m_SPP_Pos[2] = m_ApproxRecPos[2];
// must set zero of [dx,dy,dy] int Kinematic
m_Xk_1(0) = 0; m_Xk_1(1) = 0; m_Xk_1(2) = 0;
}
//save filter sate for Quality Control
MatrixXd temp_Fk_1 = m_Fk_1, temp_Qwk_1 = m_Qwk_1,
temp_Rk_1 = m_Rk_1, temp_Pk_1 = m_Pk_1;
VectorXd temp_Xk_1 = m_Xk_1;
double temp_SPP_POS[3] = {0};
memcpy(temp_SPP_POS, m_SPP_Pos, 3*sizeof(double));
// use spp clk as priori value for base clk
QKalmanFilter::KALMAN_MODEL kalman_model = getModel();
if(kalman_model == QKalmanFilter::KALMAN_MODEL::SPP_STATIC || kalman_model == QKalmanFilter::KALMAN_MODEL::SPP_KINEMATIC)
if(m_ApproxRecPos[3] != 0) m_Xk_1(3) = m_ApproxRecPos[3];// m_ApproxRecPos[3] (spp clk) must have value
else
if(m_ApproxRecPos[3] != 0) m_Xk_1(4) = m_ApproxRecPos[3];// m_ApproxRecPos[3] (spp clk) must have value
// filter
filter(preEpoch, currEpoch, X, P);
// Quality Control
bool gross_LC = true;// false
int minSatNum = 5, max_iter = 10;
if(m_KALMAN_MODEL == KALMAN_MODEL::SPP_STATIC || m_KALMAN_MODEL == KALMAN_MODEL::PPP_STATIC)
minSatNum = 1;
else
minSatNum = 5;
while(gross_LC)
{
// get B, wightP ,L
MatrixXd B, wightP;
VectorXd L, delate_LC;
if(getPPPModel() == PPP_MODEL::PPP_Combination)
Obtaining_equation(currEpoch, m_SPP_Pos, B, L, wightP);
else if(getPPPModel() == PPP_MODEL::PPP_NOCombination)
Obtaining_equation_NoCombination(currEpoch, m_SPP_Pos, B, L, wightP);
// detect gross error
int sat_len = currEpoch.length();
if(m_KALMAN_MODEL == KALMAN_MODEL::SPP_STATIC || m_KALMAN_MODEL == KALMAN_MODEL::SPP_KINEMATIC)
{