Bayesian Filtering Library
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Class for linear analytic measurementmodels with additive gaussian noise. More...
#include <linearanalyticmeasurementmodel_gaussianuncertainty.h>
Public Member Functions | |
LinearAnalyticMeasurementModelGaussianUncertainty (LinearAnalyticConditionalGaussian *pdf=NULL) | |
Constructor. More... | |
virtual MatrixWrapper::Matrix | df_dxGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x) |
Returns H-matrix. More... | |
virtual MatrixWrapper::ColumnVector | PredictionGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x) |
Returns estimation of measurement. | |
virtual MatrixWrapper::SymmetricMatrix | CovarianceGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x) |
Returns covariance on the measurement. | |
void | HSet (const MatrixWrapper::Matrix &h) |
Set Matrix H. More... | |
void | JSet (const MatrixWrapper::Matrix &j) |
Set Matrix J. More... | |
const MatrixWrapper::Matrix & | HGet () const |
Get Matrix H. | |
const MatrixWrapper::Matrix & | JGet () const |
Get Matrix J. | |
int | MeasurementSizeGet () const |
Get Measurement Size. | |
bool | SystemWithoutSensorParams () const |
Number of Conditional Arguments. | |
ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > * | MeasurementPdfGet () |
Get the MeasurementPDF. | |
void | MeasurementPdfSet (ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *pdf) |
Set the MeasurementPDF. More... | |
MatrixWrapper::ColumnVector | Simulate (const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s, const SampleMthd sampling_method=SampleMthd::DEFAULT, void *sampling_args=NULL) |
Simulate the Measurement, given a certain state, and an input. More... | |
MatrixWrapper::ColumnVector | Simulate (const MatrixWrapper::ColumnVector &x, const SampleMthd sampling_method=SampleMthd::DEFAULT, void *sampling_args=NULL) |
Simulate the system (no input system) 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... | |
Protected Attributes | |
ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > * | _MeasurementPdf |
ConditionalPdf representing ![]() | |
bool | _systemWithoutSensorParams |
System with no sensor params?? | |
Class for linear analytic measurementmodels with additive gaussian noise.
This class represents all measurementmodels of the form
Definition at line 32 of file linearanalyticmeasurementmodel_gaussianuncertainty.h.
Constructor.
Conditional pdf, with Gaussian uncertainty |
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virtual |
Returns H-matrix.
used by extended kalman filter
u | 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 AnalyticMeasurementModelGaussianUncertainty.
Reimplemented in LinearAnalyticMeasurementModelGaussianUncertainty_Implicit.
void HSet | ( | const MatrixWrapper::Matrix & | h | ) |
Set Matrix H.
This can be particularly useful for time-varying systems
h | Matrix H |
void JSet | ( | const MatrixWrapper::Matrix & | j | ) |
Set Matrix J.
This can be particularly useful for time-varying systems
j | Matrix J |
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inherited |
Set the MeasurementPDF.
a pointer to the measurement pdf |
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inherited |
Get the probability of a certain measurement.
(measurement independent of input) gived a certain state and input
z | the measurement value |
x | x current state of the system |
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inherited |
Get the probability of a certain measurement.
given a certain state and input
z | the measurement value |
x | current state of the system |
s | the sensor param value |
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inherited |
Simulate the Measurement, given a certain state, and an input.
x | current state of the system |
s | sensor parameter |
sampling_method | the sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT) |
sampling_args | Sometimes a sampling method can have some extra parameters (eg mcmc sampling) |
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inherited |
Simulate the system (no input system)
x | current state of the system |
sampling_method | the sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT) |
sampling_args | Sometimes a sampling method can have some extra parameters (eg mcmc sampling) |