This class implements an Extended Kalman filter. More...

Detailed Description

This class implements an Extended Kalman filter.

Definition at line 238 of file kalmanFilter.hpp.

Inheritance diagram for jafar::filter::ExtendedKalmanFilter:

Public Member Functions
	ExtendedKalmanFilter (std::size_t n_)
void	predict (JacobianPredictModel &m_)
	This function computes the prediction step.
void	predict (JacobianCommandPredictModel &m_, jblas::vec const &u_)
	This function computes the prediction step.
void	update (JacobianObserveModel &m_, const jblas::vec &z_)
	This function computes the observation step (innovation is given).
Protected Member Functions
void	updateExtended (const jblas::mat_range &H_, double y_, double R_)
	This function computes the observation step (innovation is given).

Member Function Documentation

void jafar::filter::ExtendedKalmanFilter::predict ( JacobianPredictModel & m_ )

This function computes the prediction step.

Parameters:

m_	linear predict model

void jafar::filter::ExtendedKalmanFilter::predict	(	JacobianCommandPredictModel &	m_,
		jblas::vec const &	u_
	)

This function computes the prediction step.

Parameters:

m_	linear predict model

void jafar::filter::ExtendedKalmanFilter::update	(	JacobianObserveModel &	m_,
		const jblas::vec &	z_
	)

This function computes the observation step (innovation is given).

Parameters:

m_	observation model
z_	observation

void jafar::filter::ExtendedKalmanFilter::updateExtended	(	const jblas::mat_range &	H_,
		double	y_,
		double	R_
	)		`[protected]`

This function computes the observation step (innovation is given).

In the case of a scalar observation.

Parameters:

H_	The observation matrix (only one row)
y_	The innovation
R_	The measure noise variance

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