ukf::state Namespace Reference

UKF for state estimation, additive noise case The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p108, PhD, van Der Merwe. More...

Classes
struct	ukf_param
	Structure holding the parameters of the statistical linearization. More...
struct	ukf_state
	Structure holding the matrices manipulated by the statistical linearization in the vectorial case for state estimation. More...
class	EvolutionNoise
	Mother class from which the evolution noises inherit. More...
class	EvolutionAnneal
	Annealing type evolution noise. More...
class	EvolutionRLS
	Forgetting type evolution noise. More...
class	EvolutionRobbinsMonro
	Robbins-Monro evolution noise. More...

Functions
void	ukf_init (ukf_param &p, ukf_state &s)
	Allocation of the vectors/matrices and initialization. More...
void	ukf_free (ukf_param &p, ukf_state &s)
	Free of memory allocation. More...
template<typename FunctProcess , typename FunctObservation >
void	ukf_iterate (ukf_param &p, ukf_state &s, FunctProcess f, FunctObservation h, gsl_vector *yi)
	UKF-additive (zero-mean) noise case, "Kalman Filtering and Neural Networks", p.233. More...
template<typename FunctProcess , typename FunctObservation >
void	ukf_evaluate (ukf_param &p, ukf_state &s, FunctProcess f, FunctObservation h, gsl_vector *yi)
	Evaluation of the output from the sigma points. More...

Detailed Description

UKF for state estimation, additive noise case The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p108, PhD, van Der Merwe.

Function Documentation

template<typename FunctProcess , typename FunctObservation >

void ukf::state::ukf_evaluate ( ukf_param &  p, ukf_state &  s, FunctProcess  f, FunctObservation  h, gsl_vector *  yi  )

inline

Evaluation of the output from the sigma points.

void ukf::state::ukf_free ( ukf_param &  p, ukf_state &  s  )

inline

Free of memory allocation.

Examples:

example-007.cc.

void ukf::state::ukf_init ( ukf_param &  p, ukf_state &  s  )

inline

Allocation of the vectors/matrices and initialization.

Examples:

example-007.cc.

template<typename FunctProcess , typename FunctObservation >

void ukf::state::ukf_iterate ( ukf_param &  p, ukf_state &  s, FunctProcess  f, FunctObservation  h, gsl_vector *  yi  )

inline

UKF-additive (zero-mean) noise case, "Kalman Filtering and Neural Networks", p.233.

Examples:

example-007.cc.