Class for linear analytic measurementmodels with additive gaussian noise. More...

#include <linearanalyticmeasurementmodel_gaussianuncertainty_implicit.h>

Inheritance diagram for BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit:

Public Member Functions
virtual void	Calculate (const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &z, const MatrixWrapper::Matrix &R)=0

virtual MatrixWrapper::SymmetricMatrix &	CovarianceGet ()=0
	Returns covariance of the noise on the linearised measurement model evaluated using measurements z and states x. More...

virtual MatrixWrapper::SymmetricMatrix	CovarianceGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
	Returns covariance of the noise on the linearised measurement model evaluated using current z and states x. More...

virtual MatrixWrapper::Matrix	df_dxGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
	Returns H-matrix calculated with measurement z and state x. More...

virtual MatrixWrapper::Matrix &	df_dzGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
	Returns D-matrix calculated with measurement z and state x. More...

virtual MatrixWrapper::Matrix &	dfGet (int number)=0

virtual MatrixWrapper::ColumnVector	ExpectedValueGet ()=0
	Return a prediction for the mean of the noise on the linear measurement equation, using the current x and z. More...

virtual const MatrixWrapper::ColumnVector &	fGet () const =0

virtual const int &	Is_Identity () const =0
	Returns 1 if D-matrix equals the identity matrix else 0. More...

	LinearAnalyticMeasurementModelGaussianUncertainty_Implicit (LinearAnalyticConditionalGaussian *pdf)
	Constructor. More...

	LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ()
	Constructor. More...

virtual MatrixWrapper::ColumnVector	PredictionGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
	Return a prediction for the mean of the noise on the linear measurement equation, calculated with measurements z and state x. More...

virtual const MatrixWrapper::Matrix &	SRCovariance () const =0
	Returns square root of the covariance of the measurements z. More...

virtual const int	TypeGet () const =0

virtual	~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ()
	Destructor. More...

Public Member Functions inherited from BFL::LinearAnalyticMeasurementModelGaussianUncertainty
const MatrixWrapper::Matrix &	HGet () const
	Get Matrix H. More...

void	HSet (const MatrixWrapper::Matrix &h)
	Set Matrix H. More...

const MatrixWrapper::Matrix &	JGet () const
	Get Matrix J. More...

void	JSet (const MatrixWrapper::Matrix &j)
	Set Matrix J. More...

	LinearAnalyticMeasurementModelGaussianUncertainty (LinearAnalyticConditionalGaussian *pdf=NULL)
	Constructor. More...

virtual	~LinearAnalyticMeasurementModelGaussianUncertainty ()

Public Member Functions inherited from BFL::AnalyticMeasurementModelGaussianUncertainty
	AnalyticMeasurementModelGaussianUncertainty (AnalyticConditionalGaussian *Measurementpdf=NULL)
	Constructor. More...

virtual	~AnalyticMeasurementModelGaussianUncertainty ()
	Destructor. More...

Public Member Functions inherited from BFL::MeasurementModel< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >
	MeasurementModel (ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *Measurementpdf=NULL)
	Constructor. More...

ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *	MeasurementPdfGet ()
	Get the MeasurementPDF. More...

void	MeasurementPdfSet (ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *pdf)
	Set the MeasurementPDF. More...

int	MeasurementSizeGet () const
	Get Measurement Size. More...

Probability	ProbabilityGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s)
	Get the probability of a certain measurement. More...

Probability	ProbabilityGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)
	Get the probability of a certain measurement. More...

MatrixWrapper::ColumnVector	Simulate (const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s, int sampling_method=DEFAULT, void *sampling_args=NULL)
	Simulate the Measurement, given a certain state, and an input. More...

MatrixWrapper::ColumnVector	Simulate (const MatrixWrapper::ColumnVector &x, int sampling_method=DEFAULT, void *sampling_args=NULL)
	Simulate the system (no input system) More...

bool	SystemWithoutSensorParams () const
	Number of Conditional Arguments. More...

virtual	~MeasurementModel ()
	Destructor. More...

Additional Inherited Members
Protected Attributes inherited from BFL::MeasurementModel< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >
ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *	_MeasurementPdf
	ConditionalPdf representing $P(Z_k \| X_{k}, U_{k})$ . More...

bool	_systemWithoutSensorParams
	System with no sensor params?? More...

Detailed Description

Class for linear analytic measurementmodels with additive gaussian noise.

This class represents all measurement models of the form

$0 = f (x,z)$

as a linear measurement model with virtual measurement z_k^{virtual}

$z_k^{virtual} = H(x_k,z_k) \times x_k + N(\mu(x_{k},z_k) ,\Sigma(x_k,z_k))$

Definition at line 37 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.h.

Constructor & Destructor Documentation

◆ LinearAnalyticMeasurementModelGaussianUncertainty_Implicit() [1/2]

BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ( LinearAnalyticConditionalGaussian * pdf )

Constructor.

Parameters

pdf	Conditional pdf, with Gaussian uncertainty

Definition at line 27 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.cpp.

◆ LinearAnalyticMeasurementModelGaussianUncertainty_Implicit() [2/2]

BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ( )

Constructor.

Definition at line 32 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.cpp.

◆ ~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit()

BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ( )

virtual

Destructor.

Definition at line 43 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.cpp.

Member Function Documentation

◆ Calculate()

virtual void BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::Calculate	(	const MatrixWrapper::ColumnVector &	x,
		const MatrixWrapper::ColumnVector &	z,
		const MatrixWrapper::Matrix &	R
	)

pure virtual

◆ CovarianceGet() [1/2]

virtual MatrixWrapper::SymmetricMatrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::CovarianceGet ( )

pure virtual

Returns covariance of the noise on the linearised measurement model evaluated using measurements z and states x.

The linearised measurement equation look like:

$z_k^{virtual} = H(x_{k},z_k) \times x_k + N(\mu(x_{k},z_k) ,\Sigma(x_k,z_k))$

with noise

$=N(\mu(x_{k},z_k), \Sigma(x_k,z_k))$

and covariance

$\Sigma(x_k,z_k)= D(x_k,z_k)*R*D(x_k,z_k)'$

and R the noise on the measurements z .

◆ CovarianceGet() [2/2]

virtual MatrixWrapper::SymmetricMatrix BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::CovarianceGet	(	const MatrixWrapper::ColumnVector &	z,
		const MatrixWrapper::ColumnVector &	x
	)

pure virtual

Returns covariance of the noise on the linearised measurement model evaluated using current z and states x.

The linearised measurement equation look like:

$z_k^{virtual} = H(x_{k},z_k) \times x_k + N(\mu(x_{k},z_k) ,\Sigma(x_k,z_k))$

with noise

$=N(\mu(x_{k},z_k), \Sigma(x_k,z_k))$

and covariance

$\Sigma(x_k,z_k)= D(x_k,z_k)*R*D(x_k,z_k)'$

and R the noise on the measurements z .

Reimplemented from BFL::LinearAnalyticMeasurementModelGaussianUncertainty.

◆ df_dxGet()

virtual MatrixWrapper::Matrix BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::df_dxGet	(	const MatrixWrapper::ColumnVector &	z,
		const MatrixWrapper::ColumnVector &	x
	)

pure virtual

Returns H-matrix calculated with measurement z and state x.

$H = \frac{df}{dx} \mid_{ z, x}$

used to determine the covariance of noise on the linear measurement equation

Parameters

z	The value of the input in which the derivate is evaluated
x	The value in the state in which the derivate is evaluated

Reimplemented from BFL::LinearAnalyticMeasurementModelGaussianUncertainty.

◆ df_dzGet()

virtual MatrixWrapper::Matrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::df_dzGet	(	const MatrixWrapper::ColumnVector &	z,
		const MatrixWrapper::ColumnVector &	x
	)

pure virtual

Returns D-matrix calculated with measurement z and state x.

$D = \frac{df}{dz} \mid_{ z, x}$

used to determine the covariance of noise on the linear measurement equation

Parameters

z	The value of the input in which the derivate is evaluated
x	The value in the state in which the derivate is evaluated

◆ dfGet()

virtual MatrixWrapper::Matrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::dfGet ( int number )

pure virtual

◆ ExpectedValueGet()

virtual MatrixWrapper::ColumnVector BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::ExpectedValueGet ( )

pure virtual

Return a prediction for the mean of the noise on the linear measurement equation, using the current x and z.

◆ fGet()

virtual const MatrixWrapper::ColumnVector& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::fGet ( ) const

pure virtual

◆ Is_Identity()

virtual const int& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::Is_Identity ( ) const

pure virtual

Returns 1 if D-matrix equals the identity matrix else 0.

◆ PredictionGet()

virtual MatrixWrapper::ColumnVector BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::PredictionGet	(	const MatrixWrapper::ColumnVector &	z,
		const MatrixWrapper::ColumnVector &	x
	)

pure virtual

Return a prediction for the mean of the noise on the linear measurement equation, calculated with measurements z and state x.

Reimplemented from BFL::LinearAnalyticMeasurementModelGaussianUncertainty.

◆ SRCovariance()

virtual const MatrixWrapper::Matrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::SRCovariance ( ) const

pure virtual

Returns square root of the covariance of the measurements z.

◆ TypeGet()

virtual const int BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::TypeGet ( ) const

pure virtual

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

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ LinearAnalyticMeasurementModelGaussianUncertainty_Implicit() [1/2]

◆ LinearAnalyticMeasurementModelGaussianUncertainty_Implicit() [2/2]

◆ ~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit()

Member Function Documentation

◆ Calculate()

◆ CovarianceGet() [1/2]

◆ CovarianceGet() [2/2]

◆ df_dxGet()

◆ df_dzGet()

◆ dfGet()

◆ ExpectedValueGet()

◆ fGet()

◆ Is_Identity()

◆ PredictionGet()

◆ SRCovariance()

◆ TypeGet()