ukf::srstate Namespace Reference

MUST NOT BE USED !!!!!!! Square root UKF for state estimation, additive noise case The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p115, 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...

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

MUST NOT BE USED !!!!!!! Square root UKF for state estimation, additive noise case The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p115, PhD, van Der Merwe.

Function Documentation

template<typename FunctProcess , typename FunctObservation >

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

inline

Free of memory allocation.

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

inline

Allocation of the vectors/matrices and initialization.

template<typename FunctProcess , typename FunctObservation >

void ukf::srstate::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.