#include <SSModel.hpp>
Public Types | |
typedef Eigen::Matrix < precission, Eigen::Dynamic, Eigen::Dynamic > | matrix |
typedef precission | numericprecission |
typedef Eigen::Matrix < precission, Eigen::Dynamic, 1 > | vector |
Public Member Functions | |
void | setState (vector x) |
SSModel () | |
Public Attributes | |
matrix | A |
matrix | B |
matrix | H |
matrix | H0 |
matrix | Q |
matrix | R |
matrix | R0 |
precission | Ts |
matrix | V |
matrix | V0 |
matrix | W |
Protected Attributes | |
vector | x |
vector | xk_1 |
This class implements a generic stochastic state space model. When implementing models try to inherit from this class. The following naming scheme is used:
x(k+1) = A*x(k) + B*u(k) + w(k) y(k) = H*x(k) + v(k)
w - model noise p(w) = N(0,Q(k)) v - measurement noise p(v) = N(0,R(k))
In the nonlinear case:
x(k+1) = f(x(k),u(k),w(k)) y(k) = h(x(k),v(k))
update the following jacobian matrices as: A = {{f}}{{x}}(x(k-1),u(k),0) W = {{f}}{{w}}(x(k-1),u(k),0) H = {{h}}{{x}}(x(k),0) V = {{h}}{{v}}(x(k),0)
We leave the matrix size generic for now. Usually these could be supplied directly in the template.
Definition at line 71 of file SSModel.hpp.
typedef Eigen::Matrix<precission, Eigen::Dynamic, Eigen::Dynamic> labust::navigation::SSModel< precission >::matrix |
Definition at line 76 of file SSModel.hpp.
typedef precission labust::navigation::SSModel< precission >::numericprecission |
Definition at line 74 of file SSModel.hpp.
typedef Eigen::Matrix<precission, Eigen::Dynamic, 1> labust::navigation::SSModel< precission >::vector |
Definition at line 77 of file SSModel.hpp.
labust::navigation::SSModel< precission >::SSModel | ( | ) | [inline] |
Main constructor.
Definition at line 86 of file SSModel.hpp.
void labust::navigation::SSModel< precission >::setState | ( | vector | x | ) | [inline] |
Sets the internal state of the model.
Definition at line 90 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::A |
State transition, Input, Model noise covariance, Model noise transformation Measurement noise covariance, Measurement noise transformation
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::B |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::H |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::H0 |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::Q |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::R |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::R0 |
Definition at line 100 of file SSModel.hpp.
precission labust::navigation::SSModel< precission >::Ts |
Model sampling time
Definition at line 104 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::V |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::V0 |
Definition at line 100 of file SSModel.hpp.
matrix labust::navigation::SSModel< precission >::W |
Definition at line 100 of file SSModel.hpp.
vector labust::navigation::SSModel< precission >::x [protected] |
Definition at line 110 of file SSModel.hpp.
vector labust::navigation::SSModel< precission >::xk_1 [protected] |
State and output vector.
Definition at line 110 of file SSModel.hpp.