filters::KalmanFilter< stateDim, inputDim, outputDim > Class Template Reference

Implements a Kalman Filter. More...

#include <KalmanFilter.h>

Inheritance diagram for filters::KalmanFilter< stateDim, inputDim, outputDim >:

Collaboration diagram for filters::KalmanFilter< stateDim, inputDim, outputDim >:

Public Member Functions
void	correct (const Eigen::Matrix< double, outputDim, 1 > &measurement)
	Correct the state estimate with measurement data.
void	predict (const Eigen::Matrix< double, inputDim, 1 > &input) override
	Use the model to predict the next system state, given the current inputs.
Public Member Functions inherited from filters::KalmanFilterBase< stateDim, inputDim >
void	reset ()
	Reset the filter.
void	reset (const Eigen::Matrix< double, stateDim, 1 > &state)
	Reset the filter.
void	reset (const Eigen::Matrix< double, stateDim, 1 > &state, const Eigen::Matrix< double, stateDim, 1 > &stdDevs)
	Reset the filter.
void	reset (const Eigen::Matrix< double, stateDim, 1 > &state, const Eigen::Matrix< double, stateDim, stateDim > &estCovMat)
	Reset the filter.
Eigen::Matrix< double, stateDim, 1 >	getState () const
	Gets the current state estimate.
Eigen::Matrix< double, stateDim, stateDim >	getEstimateCovarianceMat () const
	Get the current estimate covariance matrix.

Static Public Member Functions
static KalmanFilter	createContinuous (const Eigen::Matrix< double, stateDim, stateDim > &systemMat, const Eigen::Matrix< double, stateDim, inputDim > &inputMat, const Eigen::Matrix< double, outputDim, stateDim > &outputMat, const Eigen::Matrix< double, stateDim, 1 > &stateStdDevs, const Eigen::Matrix< double, outputDim, 1 > &measurementStdDevs, double dt)
	Create a new Kalman Filter from a continuous-time state space model.
static KalmanFilter	createDiscrete (const Eigen::Matrix< double, stateDim, stateDim > &systemMat, const Eigen::Matrix< double, stateDim, inputDim > &inputMat, const Eigen::Matrix< double, outputDim, stateDim > &outputMat, const Eigen::Matrix< double, stateDim, 1 > &stateStdDevs, const Eigen::Matrix< double, outputDim, 1 > &measurementStdDevs, double dt)
	Create a new Kalman Filter from a discrete-time state space model.

Additional Inherited Members
Protected Attributes inherited from filters::KalmanFilterBase< stateDim, inputDim >
Eigen::Matrix< double, stateDim, stateDim >	P
Eigen::Matrix< double, stateDim, 1 >	xHat

Detailed Description

template<int stateDim, int inputDim, int outputDim>
class filters::KalmanFilter< stateDim, inputDim, outputDim >

Implements a Kalman Filter.

Unlike the "standard" Kalman Filter this uses the asymptotic Kalman gain.

Template Parameters

stateDim	The dimension of the state vector.
inputDim	The dimension of the system input vector.
outputDim	The dimension of the system output vector, or the sensor measurement.

Member Function Documentation

correct()

template<int stateDim, int inputDim, int outputDim>

void filters::KalmanFilter< stateDim, inputDim, outputDim >::correct ( const Eigen::Matrix< double, outputDim, 1 > & measurement )

inline

Correct the state estimate with measurement data.

The measurement should be in the same space as the state.

Parameters

measurement

The measurement to use to correct the filter.

createContinuous()

template<int stateDim, int inputDim, int outputDim>

static KalmanFilter filters::KalmanFilter< stateDim, inputDim, outputDim >::createContinuous ( const Eigen::Matrix< double, stateDim, stateDim > & systemMat, const Eigen::Matrix< double, stateDim, inputDim > & inputMat, const Eigen::Matrix< double, outputDim, stateDim > & outputMat, const Eigen::Matrix< double, stateDim, 1 > & stateStdDevs, const Eigen::Matrix< double, outputDim, 1 > & measurementStdDevs, double dt )

inlinestatic

Create a new Kalman Filter from a continuous-time state space model.

The only matrices that change between this and createDisc() are the system matrix and input matrix. All other parameters would be the same.

Parameters

systemMat	The continuous-time system matrix.
inputMat	The continuous-time input matrix.
outputMat	The output matrix.
stateStdDevs	The standard deviations for the system model. This implies inaccuracy in the state space model.
measurementStdDevs	The standard deviations of the measurement. This implies inaccuracy in the sensor.
dt	The time in seconds between each update.

Returns

A Kalman Filter built for the specified system.

createDiscrete()

template<int stateDim, int inputDim, int outputDim>

static KalmanFilter filters::KalmanFilter< stateDim, inputDim, outputDim >::createDiscrete ( const Eigen::Matrix< double, stateDim, stateDim > & systemMat, const Eigen::Matrix< double, stateDim, inputDim > & inputMat, const Eigen::Matrix< double, outputDim, stateDim > & outputMat, const Eigen::Matrix< double, stateDim, 1 > & stateStdDevs, const Eigen::Matrix< double, outputDim, 1 > & measurementStdDevs, double dt )

inlinestatic

Create a new Kalman Filter from a discrete-time state space model.

The only matrices that change between this and createCont() are the system matrix and input matrix. All other parameters would be the same.

Parameters

systemMat	The discrete-time system matrix.
inputMat	The discrete-time input matrix.
outputMat	The output matrix.
stateStdDevs	The standard deviations for the system model. This implies inaccuracy in the state space model.
measurementStdDevs	The standard deviations of the measurement. This implies inaccuracy in the sensor.
dt	The time in seconds between each update.

Returns

A Kalman Filter built for the specified system.

predict()

template<int stateDim, int inputDim, int outputDim>

void filters::KalmanFilter< stateDim, inputDim, outputDim >::predict ( const Eigen::Matrix< double, inputDim, 1 > & input )

inlineoverridevirtual

Use the model to predict the next system state, given the current inputs.

Parameters

input

The current inputs to the system.

Implements filters::KalmanFilterBase< stateDim, inputDim >.

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

• src/filters/KalmanFilter.h