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https://github.com/gnss-sdr/gnss-sdr
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ADD: vtl_engine persistent variables
This commit is contained in:
M.A.Gomez
parent
759e31e8f7
commit
44cc402766
138
src/algorithms/PVT/libs/vtl_engine.cc
Normal file → Executable file
138
src/algorithms/PVT/libs/vtl_engine.cc
Normal file → Executable file
@ -27,6 +27,144 @@ Vtl_Engine::~Vtl_Engine()
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bool Vtl_Engine::vtl_loop(Vtl_Data new_data)
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bool Vtl_Engine::vtl_loop(Vtl_Data new_data)
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{
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{
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//TODO: Implement main VTL loop here
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//TODO: Implement main VTL loop here
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// // ################## Kalman filter initialization ######################################
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// // covariances (static)
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// kf_P_x_ini = arma::zeros(8, 8);
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// kf_x_pri = arma::zeros(8, 1);
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// kf_R = arma::zeros(2*n_sats, 2*n_sats);
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// kf_dt=1e-3;
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// kf_Q = arma::zeros(8, 8);
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// kf_F = arma::zeros(8, 8);
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// kf_F(0, 0) = 1.0; kf_F(0, 3) = kf_dt;
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// kf_F(1, 1) = 1.0; kf_F(1, 4) = kf_dt;
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// kf_F(2, 2) = 1.0; kf_F(2, 5) = kf_dt;
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// kf_F(3, 3) = 1.0;
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// kf_F(4, 4) = 1.0;
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// kf_F(5, 5) = 1.0;
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// kf_F(6, 6) = 1.0; kf_F(6, 7) = kf_dt;
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// kf_F(7, 7) = 1.0;
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// kf_H = arma::zeros(8, 2*n_sats);
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// kf_x = arma::zeros(8, 1);
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// kf_y = arma::zeros(2*n_sats, 1);
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// kf_P_y = arma::zeros(2*n_sats, 2*n_sats);
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// // ################## Kalman Tracking ######################################
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// // receiver solution from rtklib_solver
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// kf_x(0)=new_vtl_data.rx_p(0);
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// kf_x(1)=new_vtl_data.rx_p(1);
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// kf_x(2)=new_vtl_data.rx_p(2);
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// kf_x(3)=new_vtl_data.rx_v(0);
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// kf_x(4)=new_vtl_data.rx_v(1);
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// kf_x(5)=new_vtl_data.rx_v(2);
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// kf_x(6)=new_vtl_data.rx_dts(0);
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// kf_x(7)=new_vtl_data.rx_dts(1);
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// // Kalman state prediction (time update)
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// kf_x_pri = kf_F * kf_x; // state prediction
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// //kf_P_x_pri = kf_F * kf_P_x * kf_F.t() + kf_Q; // state error covariance prediction
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// //from error state variables to variables
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// //x_u=x_u0+kf_x_pri(0);
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// //y_u=y_u0+kf_x_pri(1);
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// //z_u=z_u0+kf_x_pri(2);
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// //xDot_u=xDot_u0+kf_x_pri(3);
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// //yDot_u=yDot_u0+kf_x_pri(4);
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// //zDot_u=zDot_u0+kf_x_pri(5);
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// //cdeltat_u=cdeltat_u0+kf_x_pri(6);
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// //cdeltatDot_u=cdeltatDot_u+kf_x_pri(7);
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// //from state variables definition
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// x_u=kf_x_pri(0);
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// y_u=kf_x_pri(1);
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// z_u=kf_x_pri(2);
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// xDot_u=kf_x_pri(3);
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// yDot_u=kf_x_pri(4);
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// zDot_u=kf_x_pri(5);
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// cdeltat_u=kf_x_pri(6);
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// cdeltatDot_u=kf_x_pri(7);
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// for (int32_t i = 0; i < n_sats; n++) //neccesary quantities
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// {
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// d(i)=sqrt(square(new_vtl_data.sat_p(i, 0)-x_u)+square(new_vtl_data.sat_p(i, 1)-y_u)+square(new_vtl_data.sat_p(i, 2)-z_u));
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// //compute pseudorange estimation
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// rho_pri(i)=d(i)+cdeltat_u;
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// //compute LOS sat-receiver vector components
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// a_x(i)=-(new_vtl_data.sat_p(i, 0)-x_u)/d(i);
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// a_y(i)=-(new_vtl_data.sat_p(i, 1)-y_u)/d(i);;
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// a_z(i)=-(new_vtl_data.sat_p(i, 2)-z_u)/d(i);;
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// //compute pseudorange rate estimation
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// rhoDot_pri(i)=(new_vtl_data.sat_v(i, 0)-xDot_u)*a_x(i)+(new_vtl_data.sat_v(i, 1)-yDot_u)*a_y(i)+(new_vtl_data.sat_v(i, 2)-zDot_u)*a_z(i)+cdeltatDot_u;
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// }
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// kf_H = arma::zeros(8, 2*n_sats);
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// for (int32_t i = 0; i < n_sats; n++) // Measurement matrix H assembling
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// {
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// // It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error)
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// kf_H(i, 0) = a_x(i); kf_H(i, 1) = a_y(i); kf_H(i, 2) = a_z(i); kf_H(i, 6) = 1.0;
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// kf_H(i+n_sats, 3) = a_x(i); kf_H(i+n_sats, 4) = a_y(i); kf_H(i+n_sats, 5) = a_z(i); kf_H(i+n_sats, 7) = 1.0;
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// }
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// // Kalman estimation (measurement update)
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// for (int32_t i = 0; i < n_sats; n++) // Measurement vector
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// {
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// kf_y(i) = delta_rho(i); // i-Satellite
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// kf_y(i+n_sats) = delta_rhoDot(i); // i-Satellite
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// }
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// for (int32_t i = 0; i < n_sats; n++) // Measurement error Covariance Matrix R assembling
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// {
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// // It is diagonal 2*NSatellite x 2*NSatellite (NSat psudorange error;NSat pseudo range rate error)
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// kf_R(i, i) = 1.0;
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// kf_R(i+n_sats, i+n_sats) = 1.0;
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// }
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// // Kalman filter update step
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// // kf_P_y = kf_H * kf_P_x_pri * kf_H.t() + kf_R; // innovation covariance matrix (S)
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// // kf_K = (kf_P_x_pri * kf_H.t()) * arma::inv(kf_P_y); // Kalman gain
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// for (int32_t i = 0; i < n_sats; n++) //Error measurement vector
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// {
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// // kf_delta_y(i)=rho(i)+delta_rho(i)-rho_pri(i); // pseudorange error
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// // kf_delta_y(i+n_sats)=rhoDot(i)+delta_F*(-lambdaC)-rhoDot_pri(i); // pseudorange rate error
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// }
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// // kf_delta_x = kf_K * kf_delta_y; // updated error state estimation
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// // kf_P_x = (arma::eye(size(kf_P_x_pri)) - kf_K * kf_H) * kf_P_x_pri; // update state estimation error covariance matrix
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// // kf_x = kf_x_pri+kf_delta_x; // compute PVT from priori and error estimation (neccesary?)
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// // ################## Geometric Transformation ######################################
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// for (int32_t i = 0; i < n_sats; n++) //neccesary quantities at posteriori
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// {
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// //compute pseudorange posteriori estimation
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// // rho_est(i)=;
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// //compute LOS sat-receiver vector components posteriori
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// // a_x(i)=;
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// // a_y(i)=;
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// // a_z(i)=;
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// //compute pseudorange rate posteriori estimation
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// // rhoDot_est(i)=;
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// }
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// kf_H = arma::zeros(8, 2*n_sats);
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// for (int32_t i = 0; i < n_sats; n++) // Measurement matrix H posteriori assembling
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// {
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// // It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error)
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// kf_H(i, 0) = a_x(i); kf_H(i, 1) = a_y(i); kf_H(i, 2) = a_z(i); kf_H(i, 6) = 1.0;
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// kf_H(i+n_sats, 3) = a_x(i); kf_H(i+n_sats, 4) = a_y(i); kf_H(i+n_sats, 5) = a_z(i); kf_H(i+n_sats, 7) = 1.0;
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// }
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// //Re-calculate error measurement vector with the most recent data available
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// //kf_delta_y=kf_H*kf_delta_x
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// //Filtered pseudorange error measurement (in m):
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// //delta_rho_filt=;
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// //Filtered Doppler error measurement (in Hz):
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// //delta_doppler_filt=;
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//TODO: Fill the tracking commands outputs
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//TODO: Fill the tracking commands outputs
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// Notice: keep the same satellite order as in the Vtl_Data matrices
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// Notice: keep the same satellite order as in the Vtl_Data matrices
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18
src/algorithms/PVT/libs/vtl_engine.h
Normal file → Executable file
18
src/algorithms/PVT/libs/vtl_engine.h
Normal file → Executable file
@ -50,6 +50,24 @@ public:
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private:
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private:
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Vtl_Conf config;
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Vtl_Conf config;
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//TODO: Internal VTL persistent variables here
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//TODO: Internal VTL persistent variables here
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// Kalman filter variables
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arma::mat kf_P_x_ini; // initial state error covariance matrix
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arma::mat kf_P_x; // state error covariance matrix
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arma::mat kf_P_x_pre; // Predicted state error covariance matrix
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arma::mat kf_P_y; // innovation covariance matrix
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arma::mat kf_F; // state transition matrix
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arma::mat kf_H; // system matrix
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arma::mat kf_R; // measurement error covariance matrix
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arma::mat kf_Q; // system error covariance matrix
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arma::colvec kf_x; // state vector
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arma::colvec kf_x_pre; // predicted state vector
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arma::colvec kf_y; // measurement vector
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arma::mat kf_K; // Kalman gain matrix
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// Gaussian estimator
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arma::mat kf_R_est; // measurement error covariance
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};
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};
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