TinyEKF Class Reference

#include <TinyEKF.h>

Inheritance diagram for TinyEKF:

Public Member Functions
double	getX (int i)
void	setX (int i, double value)
bool	step (double *z)

Protected Member Functions
	TinyEKF ()
	~TinyEKF ()
virtual void	model (double fx[Nsta], double F[Nsta][Nsta], double hx[Mobs], double H[Mobs][Nsta])=0
void	setP (int i, int j, double value)
void	setQ (int i, int j, double value)
void	setR (int i, int j, double value)

Protected Attributes
double *	x

Detailed Description

A header-only class for the Extended Kalman Filter. Your implementing class should #define the constant N and and then #include <TinyEKF.h> You will also need to implement a model() method for your application.

Constructor & Destructor Documentation

TinyEKF()

TinyEKF::TinyEKF ( )

inlineprotected

Initializes a TinyEKF object.

~TinyEKF()

TinyEKF::~TinyEKF ( )

inlineprotected

Deallocates memory for a TinyEKF object.

Member Function Documentation

getX()

double TinyEKF::getX ( int  i )

inline

Returns the state element at a given index.

Parameters

i	the index (at least 0 and less than n

Returns

state value at index

model()

virtual void TinyEKF::model ( double  fx[Nsta], double  F[Nsta][Nsta], double  hx[Mobs], double  H[Mobs][Nsta]  )

protectedpure virtual

Implement this function for your EKF model.

Parameters

fx	gets output of state-transition function f(x0 .. n-1)
F	gets n × n Jacobian of f(x)
hx	gets output of observation function h(x0 .. n-1)
H	gets m × n Jacobian of h(x)

Implemented in ChassisKalman, and WheelKalman.

setP()

void TinyEKF::setP ( int  i, int  j, double  value  )

inlineprotected

Sets the specified value of the prediction error covariance. P_i,j = value

Parameters

i	row index
j	column index
value	value to set

setQ()

void TinyEKF::setQ ( int  i, int  j, double  value  )

inlineprotected

Sets the specified value of the process noise covariance. Q_i,j = value

Parameters

i	row index
j	column index
value	value to set

setR()

void TinyEKF::setR ( int  i, int  j, double  value  )

inlineprotected

Sets the specified value of the observation noise covariance. R_i,j = value

Parameters

i	row index
j	column index
value	value to set

setX()

void TinyEKF::setX ( int  i, double  value  )

inline

Sets the state element at a given index.

Parameters

i	the index (at least 0 and less than n
value	value to set

step()

bool TinyEKF::step ( double *  z )

inline

Performs one step of the prediction and update.

Parameters

z	observation vector, length m

Returns

true on success, false on failure caused by non-positive-definite matrix.

Member Data Documentation

x

double* TinyEKF::x

protected

The current state.

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

• core/util/algorithms/ekf/TinyEKF.h