#include <kalman.h>

Inheritance diagram for sp::EKF:

Collaboration diagram for sp::EKF:

Public Member Functions
	EKF (arma::uword _N, arma::uword _M, arma::uword _L)

void	set_diff_step (double _dx)

void	set_state_jac (fcn_m _f)

void	set_meas_jac (fcn_m _h)

void	jacobian_diff (arma::mat &_F, fcn_v _f, const arma::mat &_x)

void	jacobian_diff (arma::mat &_F, fcn_v _f)

void	jacobian_analytical (arma::mat &_F, fcn_m _f_m, const arma::mat &_x)

void	jacobian_analytical (arma::mat &_F, fcn_m _f_m)

void	predict (const arma::mat u)

void	predict (void)

void	update (const arma::mat z)

void	rts_smooth (const arma::mat &Xf, const arma::cube &Pf, arma::mat &Xs, arma::cube &Ps)

Public Member Functions inherited from sp::KF
	KF (arma::uword _N, arma::uword _M, arma::uword _L)

	~KF ()

void	clear (void)

void	set_state_vec (const arma::mat &_x)

void	set_trans_mat (const arma::mat &_A)

void	set_control_mat (const arma::mat &_B)

void	set_meas_mat (const arma::mat &_H)

void	set_err_cov (const arma::mat &_P)

void	set_proc_noise (const arma::mat &_Q)

void	set_meas_noise (const arma::mat &_R)

void	set_kalman_gain (const arma::mat &_K)

void	set_trans_fcn (fcn_v _f)

void	set_meas_fcn (fcn_v _h)

arma::mat	get_state_vec (void)

arma::mat	get_err (void)

arma::mat	get_kalman_gain (void)

arma::mat	get_err_cov (void)

void	predict (const arma::mat u)

void	predict (void)

void	update (const arma::mat z)

void	rts_smooth (const arma::mat &Xf, const arma::cube &Pf, arma::mat &Xs, arma::cube &Ps)

Protected Attributes
fcn_m	f_jac

fcn_m	h_jac

double	dx

Protected Attributes inherited from sp::KF
arma::uword	N

arma::uword	M

arma::uword	L

bool	lin_proc

bool	lin_meas

arma::mat	x

arma::mat	z_err

arma::mat	A

arma::mat	B

arma::mat	H

arma::mat	P

arma::mat	Q

arma::mat	R

arma::mat	K

fcn_v	f

fcn_v	h

Detailed Description

Implements Kalman functions for the discrete system with additive noise

\[ x_k = f(x_{k-1})+Bu_{k-1} + w_{k-1} \]

and with measurements

\[ z_k = h(x_k) + v_k \]

where f(x) and h(x) may be nonlinear functions. The predicting stage is

\[ \hat{x}^-_k = A\hat{x}_{k-1}+Bu_{k-1} \]

\[ P^-_k = AP_{k-1}A^T+Q \]

and the updates stage

\[ K_k = P^-_kH^T(HP^-_kH^T+R)^{-1} \]

\[ \hat{x}_k = \hat{x}^-_k + K_k(z_k-H\hat{x}^-_k) \]

\[ P_k = (I-K_kH)P^-_k \]

Where A and H is the Jacobians of f(x) and h(x) functions.

Definition at line 332 of file kalman.h.

The documentation for this class was generated from the following file:

Public Member Functions