diff --git a/src/algorithms/PVT/libs/vtl_engine.cc b/src/algorithms/PVT/libs/vtl_engine.cc index b0d031444..ea8abf83a 100755 --- a/src/algorithms/PVT/libs/vtl_engine.cc +++ b/src/algorithms/PVT/libs/vtl_engine.cc @@ -27,44 +27,46 @@ Vtl_Engine::~Vtl_Engine() bool Vtl_Engine::vtl_loop(Vtl_Data new_data) { //TODO: Implement main VTL loop here + using arma::as_scalar; + using arma::dot; // // ################## Kalman filter initialization ###################################### // // covariances (static) -// kf_P_x_ini = arma::zeros(8, 8); -// kf_x_pri = arma::zeros(8, 1); -// kf_R = arma::zeros(2*n_sats, 2*n_sats); -// kf_dt=1e-3; -// kf_Q = arma::zeros(8, 8); + kf_P_x_ini = arma::zeros(8, 8); //TODO: use a real value. + kf_x = arma::zeros(8, 1); + kf_R = arma::zeros(2*new_data.sat_number, 2*new_data.sat_number); + double kf_dt=1e-3; + kf_Q = arma::zeros(8, 8); -// kf_F = arma::zeros(8, 8); -// kf_F(0, 0) = 1.0; kf_F(0, 3) = kf_dt; -// kf_F(1, 1) = 1.0; kf_F(1, 4) = kf_dt; -// kf_F(2, 2) = 1.0; kf_F(2, 5) = kf_dt; -// kf_F(3, 3) = 1.0; -// kf_F(4, 4) = 1.0; -// kf_F(5, 5) = 1.0; -// kf_F(6, 6) = 1.0; kf_F(6, 7) = kf_dt; -// kf_F(7, 7) = 1.0; + kf_F = arma::zeros(8, 8); + kf_F(0, 0) = 1.0; kf_F(0, 3) = kf_dt; + kf_F(1, 1) = 1.0; kf_F(1, 4) = kf_dt; + kf_F(2, 2) = 1.0; kf_F(2, 5) = kf_dt; + kf_F(3, 3) = 1.0; + kf_F(4, 4) = 1.0; + kf_F(5, 5) = 1.0; + kf_F(6, 6) = 1.0; kf_F(6, 7) = kf_dt; + kf_F(7, 7) = 1.0; -// kf_H = arma::zeros(8, 2*n_sats); -// kf_x = arma::zeros(8, 1); -// kf_y = arma::zeros(2*n_sats, 1); -// kf_P_y = arma::zeros(2*n_sats, 2*n_sats); + kf_H = arma::zeros(8, 2*new_data.sat_number); + kf_x = arma::zeros(8, 1); + kf_y = arma::zeros(2*new_data.sat_number, 1); + kf_S = arma::zeros(2*new_data.sat_number, 2*new_data.sat_number); // kf_P_y innovation covariance matrix // // ################## Kalman Tracking ###################################### // // receiver solution from rtklib_solver -// kf_x(0)=new_vtl_data.rx_p(0); -// kf_x(1)=new_vtl_data.rx_p(1); -// kf_x(2)=new_vtl_data.rx_p(2); -// kf_x(3)=new_vtl_data.rx_v(0); -// kf_x(4)=new_vtl_data.rx_v(1); -// kf_x(5)=new_vtl_data.rx_v(2); -// kf_x(6)=new_vtl_data.rx_dts(0); -// kf_x(7)=new_vtl_data.rx_dts(1); + kf_x(0)=new_data.rx_p(0); + kf_x(1)=new_data.rx_p(1); + kf_x(2)=new_data.rx_p(2); + kf_x(3)=new_data.rx_v(0); + kf_x(4)=new_data.rx_v(1); + kf_x(5)=new_data.rx_v(2); + kf_x(6)=new_data.rx_dts(0); + kf_x(7)=new_data.rx_dts(1); // // Kalman state prediction (time update) -// kf_x_pri = kf_F * kf_x; // state prediction -// //kf_P_x_pri = kf_F * kf_P_x * kf_F.t() + kf_Q; // state error covariance prediction + kf_x = kf_F * kf_x; // state prediction + kf_P_x= kf_F * kf_P_x * kf_F.t() + kf_Q; // state error covariance prediction // //from error state variables to variables // //x_u=x_u0+kf_x_pri(0); @@ -75,70 +77,81 @@ bool Vtl_Engine::vtl_loop(Vtl_Data new_data) // //zDot_u=zDot_u0+kf_x_pri(5); // //cdeltat_u=cdeltat_u0+kf_x_pri(6); // //cdeltatDot_u=cdeltatDot_u+kf_x_pri(7); -// //from state variables definition -// x_u=kf_x_pri(0); -// y_u=kf_x_pri(1); -// z_u=kf_x_pri(2); -// xDot_u=kf_x_pri(3); -// yDot_u=kf_x_pri(4); -// zDot_u=kf_x_pri(5); -// cdeltat_u=kf_x_pri(6); -// cdeltatDot_u=kf_x_pri(7); -// for (int32_t i = 0; i < n_sats; n++) //neccesary quantities -// { -// 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)); -// //compute pseudorange estimation -// rho_pri(i)=d(i)+cdeltat_u; -// //compute LOS sat-receiver vector components -// a_x(i)=-(new_vtl_data.sat_p(i, 0)-x_u)/d(i); -// a_y(i)=-(new_vtl_data.sat_p(i, 1)-y_u)/d(i);; -// a_z(i)=-(new_vtl_data.sat_p(i, 2)-z_u)/d(i);; -// //compute pseudorange rate estimation -// 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; -// } +// From state variables definition + x_u=kf_x(0); + y_u=kf_x(1); + z_u=kf_x(2); + xDot_u=kf_x(3); + yDot_u=kf_x(4); + zDot_u=kf_x(5); + cdeltat_u=kf_x(6); + cdeltatDot_u=kf_x(7); -// kf_H = arma::zeros(8, 2*n_sats); + d = arma::zeros(new_data.sat_number, 1); + rho_pri = arma::zeros(new_data.sat_number, 1); + rhoDot_pri = arma::zeros(new_data.sat_number, 1); + a_x = arma::zeros(new_data.sat_number, 1); + a_y = arma::zeros(new_data.sat_number, 1); + a_z = arma::zeros(new_data.sat_number, 1); -// for (int32_t i = 0; i < n_sats; n++) // Measurement matrix H assembling -// { -// // It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error) -// 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; -// 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; -// } + for (int32_t i = 0; i < new_data.sat_number; i++) //neccesary quantities + { + d(i)=(sqrt((new_data.sat_p(i, 0)-x_u)*(new_data.sat_p(i, 0)-x_u)+(new_data.sat_p(i, 1)-y_u)*(new_data.sat_p(i, 1)-y_u)+(new_data.sat_p(i, 2)-z_u)*(new_data.sat_p(i, 2)-z_u))); + //compute pseudorange estimation + rho_pri(i)=d(i)+cdeltat_u; + //compute LOS sat-receiver vector components + a_x(i)=-(new_data.sat_p(i, 0)-x_u)/d(i); + a_y(i)=-(new_data.sat_p(i, 1)-y_u)/d(i);; + a_z(i)=-(new_data.sat_p(i, 2)-z_u)/d(i);; + //compute pseudorange rate estimation + rhoDot_pri(i)=(new_data.sat_v(i, 0)-xDot_u)*a_x(i)+(new_data.sat_v(i, 1)-yDot_u)*a_y(i)+(new_data.sat_v(i, 2)-zDot_u)*a_z(i)+cdeltatDot_u; + } -// // Kalman estimation (measurement update) -// for (int32_t i = 0; i < n_sats; n++) // Measurement vector -// { -// kf_y(i) = delta_rho(i); // i-Satellite -// kf_y(i+n_sats) = delta_rhoDot(i); // i-Satellite -// } + kf_H = arma::zeros(8, 2*new_data.sat_number); -// for (int32_t i = 0; i < n_sats; n++) // Measurement error Covariance Matrix R assembling -// { -// // It is diagonal 2*NSatellite x 2*NSatellite (NSat psudorange error;NSat pseudo range rate error) -// kf_R(i, i) = 1.0; -// kf_R(i+n_sats, i+n_sats) = 1.0; -// } + for (int32_t i = 0; i < new_data.sat_number; i++) // Measurement matrix H assembling + { + // It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error) + 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; + kf_H(i+new_data.sat_number, 3) = a_x(i); kf_H(i+new_data.sat_number, 4) = a_y(i); kf_H(i+new_data.sat_number, 5) = a_z(i); kf_H(i+new_data.sat_number, 7) = 1.0; + } -// // Kalman filter update step -// // kf_P_y = kf_H * kf_P_x_pri * kf_H.t() + kf_R; // innovation covariance matrix (S) -// // kf_K = (kf_P_x_pri * kf_H.t()) * arma::inv(kf_P_y); // Kalman gain + // Kalman estimation (measurement update) + for (int32_t i = 0; i < new_data.sat_number; i++) // Measurement vector + { + //kf_y(i) = delta_rho(i); // i-Satellite + kf_y(i)=new_data.pr_m(i); + //kf_y(i+new_data.sat_number) = delta_rhoDot(i); // i-Satellite + kf_y(i+new_data.sat_number)=new_data.doppler_hz(i); + } + + for (int32_t i = 0; i < new_data.sat_number; i++) // Measurement error Covariance Matrix R assembling + { + // It is diagonal 2*NSatellite x 2*NSatellite (NSat psudorange error;NSat pseudo range rate error) + kf_R(i, i) = 1.0; //TODO: use a real value. + kf_R(i+new_data.sat_number, i+new_data.sat_number) = 1.0; + } + + // Kalman filter update step + kf_S = kf_H * kf_P_x* kf_H.t() + kf_R; // innovation covariance matrix (S) + kf_K = (kf_P_x * kf_H.t()) * arma::inv(kf_S); // Kalman gain -// for (int32_t i = 0; i < n_sats; n++) //Error measurement vector -// { -// // kf_delta_y(i)=rho(i)+delta_rho(i)-rho_pri(i); // pseudorange error -// // kf_delta_y(i+n_sats)=rhoDot(i)+delta_F*(-lambdaC)-rhoDot_pri(i); // pseudorange rate error -// } + //for (int32_t i = 0; i < new_data.sat_number; i++) //Error measurement vector + //{ + // kf_delta_y(i)=new_data.pr_m(i)+delta_rho(i)-rho_pri(i); // pseudorange error + // kf_delta_y(i+new_data.sat_number)=new_data.doppler_hz(i)+delta_F*(-lambdaC)-rhoDot_pri(i); // pseudorange rate error + //} -// // kf_delta_x = kf_K * kf_delta_y; // updated error state estimation -// // kf_P_x = (arma::eye(size(kf_P_x_pri)) - kf_K * kf_H) * kf_P_x_pri; // update state estimation error covariance matrix + //kf_delta_x = kf_K * kf_delta_y; // updated error state estimation + kf_x = kf_K * (kf_y-dot(kf_H,kf_x)); // updated error state estimation + kf_P_x = (arma::eye(size(kf_P_x)) - kf_K * kf_H) * kf_P_x; // update state estimation error covariance matrix // // kf_x = kf_x_pri+kf_delta_x; // compute PVT from priori and error estimation (neccesary?) // // ################## Geometric Transformation ###################################### -// for (int32_t i = 0; i < n_sats; n++) //neccesary quantities at posteriori +// for (int32_t i = 0; i < new_data.sat_number; n++) //neccesary quantities at posteriori // { // //compute pseudorange posteriori estimation // // rho_est(i)=; @@ -150,13 +163,13 @@ bool Vtl_Engine::vtl_loop(Vtl_Data new_data) // // rhoDot_est(i)=; // } -// kf_H = arma::zeros(8, 2*n_sats); +// kf_H = arma::zeros(8, 2*new_data.sat_number); -// for (int32_t i = 0; i < n_sats; n++) // Measurement matrix H posteriori assembling +// for (int32_t i = 0; i < new_data.sat_number; n++) // Measurement matrix H posteriori assembling // { // // It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error) // 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; -// 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; +// kf_H(i+new_data.sat_number, 3) = a_x(i); kf_H(i+new_data.sat_number, 4) = a_y(i); kf_H(i+new_data.sat_number, 5) = a_z(i); kf_H(i+new_data.sat_number, 7) = 1.0; // } // //Re-calculate error measurement vector with the most recent data available