mrs_lib::NCUKF< n_states, n_inputs, n_measurements > Class Template Reference

Inheritance diagram for mrs_lib::NCUKF< n_states, n_inputs, n_measurements >:

Collaboration diagram for mrs_lib::NCUKF< n_states, n_inputs, n_measurements >:

Public Types
using	Base_class = UKF<n, m, p>
using	x_t = typename Base_class::x_t
using	u_t = typename Base_class::u_t
using	z_t = typename Base_class::z_t
using	P_t = typename Base_class::P_t
using	R_t = typename Base_class::R_t
using	Q_t = typename Base_class::Q_t
using	statecov_t = typename Base_class::statecov_t
using	transition_model_t = typename Base_class::transition_model_t
using	observation_model_t = typename Base_class::observation_model_t
using	X_t = typename Base_class::X_t
using	Z_t = typename Base_class::Z_t
using	Pzz_t = typename Base_class::Pzz_t
using	K_t = typename Base_class::K_t
Public Types inherited from mrs_lib::UKF< n_states, n_inputs, n_measurements >
using	x_t = typename Base_class::x_t
	state vector n*1 typedef
using	u_t = typename Base_class::u_t
	input vector m*1 typedef
using	z_t = typename Base_class::z_t
	measurement vector p*1 typedef
using	P_t = typename Base_class::P_t
	state covariance n*n typedef
using	R_t = typename Base_class::R_t
	measurement covariance p*p typedef
using	Q_t = typename Base_class::Q_t
	process covariance n*n typedef
using	W_t = typename Eigen::Matrix<double, w, 1>
	weights vector (2n+1)*1 typedef
using	statecov_t = typename Base_class::statecov_t
	typedef of a helper struct for state and covariance
using	transition_model_t = typename std::function<x_t(const x_t&, const u_t&, double)>
	function of the state transition model typedef
using	observation_model_t = typename std::function<z_t(const x_t&)>
	function of the observation model typedef

Public Member Functions
	NCUKF (const transition_model_t &transition_model, const observation_model_t &observation_model, const double l, const double alpha=1e-3, const double kappa=1, const double beta=2)
virtual statecov_t	correct (const statecov_t &sc, const z_t &z, const R_t &R) const override
Public Member Functions inherited from mrs_lib::UKF< n_states, n_inputs, n_measurements >
	UKF ()
	Convenience default constructor.
	UKF (const transition_model_t &transition_model, const observation_model_t &observation_model, const double alpha=1e-3, const double kappa=1, const double beta=2)
	The main constructor.
virtual statecov_t	correct (const statecov_t &sc, const z_t &z, const R_t &R) const override
	Implements the state correction step (measurement update).
virtual statecov_t	predict (const statecov_t &sc, const u_t &u, const Q_t &Q, double dt) const override
	Implements the state prediction step (time update).
void	setConstants (const double alpha, const double kappa, const double beta)
	Changes the Unscented Transform parameters.
void	setTransitionModel (const transition_model_t &transition_model)
	Changes the transition model function.
void	setObservationModel (const observation_model_t &observation_model)
	Changes the observation model function.

Static Public Attributes
static const int	n = n_states
static const int	m = n_inputs
static const int	p = n_measurements

Protected Member Functions
virtual K_t	computeKalmanGain (const x_t &x, const z_t &inn, const K_t &Pxz, const Pzz_t &Pzz) const override
Protected Member Functions inherited from mrs_lib::UKF< n_states, n_inputs, n_measurements >
void	computeWeights ()
X_t	computeSigmas (const x_t &x, const P_t &P) const
P_t	computePaSqrt (const P_t &P) const
Pzz_t	computeInverse (const Pzz_t &Pzz) const

Protected Attributes
double	l
Protected Attributes inherited from mrs_lib::UKF< n_states, n_inputs, n_measurements >
double	m_alpha
double	m_kappa
double	m_beta
double	m_lambda
W_t	m_Wm
W_t	m_Wc
transition_model_t	m_transition_model
observation_model_t	m_observation_model

Additional Inherited Members
Protected Types inherited from mrs_lib::UKF< n_states, n_inputs, n_measurements >
using	Base_class = KalmanFilter<n, m, p>
	Base class of this class.
using	X_t = typename Eigen::Matrix<double, n, w>
	State sigma points matrix.
using	Z_t = typename Eigen::Matrix<double, p, w>
	Measurement sigma points matrix.
using	Pzz_t = typename Eigen::Matrix<double, p, p>
	Pzz helper matrix.
using	K_t = typename Eigen::Matrix<double, n, p>
	Kalman gain matrix.
Static Protected Attributes inherited from mrs_lib::UKF< n_states, n_inputs, n_measurements >
static constexpr int	n = n_states
	Length of the state vector of the system.
static constexpr int	m = n_inputs
	Length of the input vector of the system.
static constexpr int	p = n_measurements
	Length of the measurement vector of the system.
static constexpr int	w = 2 * n + 1
	Number of sigma points/weights.

Member Function Documentation

computeKalmanGain()

template<int n_states, int n_inputs, int n_measurements>

virtual K_t mrs_lib::NCUKF< n_states, n_inputs, n_measurements >::computeKalmanGain ( const x_t & x, const z_t & inn, const K_t & Pxz, const Pzz_t & Pzz ) const

inlineoverrideprotectedvirtual

Reimplemented from mrs_lib::UKF< n_states, n_inputs, n_measurements >.

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

• /home/runner/work/mrs_lib/mrs_lib/include/mrs_lib/nckf.h