org.apache.commons.math3.filter

Class DefaultMeasurementModel

java.lang.Object

org.apache.commons.math3.filter.DefaultMeasurementModel

All Implemented Interfaces:

MeasurementModel

public class DefaultMeasurementModel
extends java.lang.Object
implements MeasurementModel

Default implementation of a MeasurementModel for the use with a KalmanFilter.

Since:

3.0

Field Summary

Fields

Modifier and Type	Field and Description
private RealMatrix	measurementMatrix The measurement matrix, used to associate the measurement vector to the internal state estimation vector.
private RealMatrix	measurementNoise The measurement noise covariance matrix.

Constructor Summary

Constructors

Constructor and Description
DefaultMeasurementModel(double[][] measMatrix, double[][] measNoise) Create a new MeasurementModel, taking double arrays as input parameters for the respective measurement matrix and noise.
DefaultMeasurementModel(RealMatrix measMatrix, RealMatrix measNoise) Create a new MeasurementModel, taking RealMatrix objects as input parameters for the respective measurement matrix and noise.

Method Summary

Methods

Modifier and Type	Method and Description
RealMatrix	getMeasurementMatrix() Returns the measurement matrix.
RealMatrix	getMeasurementNoise() Returns the measurement noise matrix.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

measurementMatrix

private RealMatrix measurementMatrix

The measurement matrix, used to associate the measurement vector to the internal state estimation vector.

measurementNoise

private RealMatrix measurementNoise

The measurement noise covariance matrix.

Constructor Detail

DefaultMeasurementModel

public DefaultMeasurementModel(double[][] measMatrix,
                       double[][] measNoise)
                        throws NullArgumentException,
                               NoDataException,
                               DimensionMismatchException

Create a new MeasurementModel, taking double arrays as input parameters for the respective measurement matrix and noise.

Parameters:

measMatrix - the measurement matrix

measNoise - the measurement noise matrix

Throws:

NullArgumentException - if any of the input matrices is null

NoDataException - if any row / column dimension of the input matrices is zero

DimensionMismatchException - if any of the input matrices is non-rectangular

DefaultMeasurementModel

public DefaultMeasurementModel(RealMatrix measMatrix,
                       RealMatrix measNoise)

Create a new MeasurementModel, taking RealMatrix objects as input parameters for the respective measurement matrix and noise.

Parameters:

measMatrix - the measurement matrix

measNoise - the measurement noise matrix

Method Detail

getMeasurementMatrix

public RealMatrix getMeasurementMatrix()

Returns the measurement matrix.

Specified by:

getMeasurementMatrix in interface MeasurementModel

Returns:

the measurement matrix

getMeasurementNoise

public RealMatrix getMeasurementNoise()

Returns the measurement noise matrix. This method is called by the KalmanFilter every correction step, so implementations of this interface may return a modified measurement noise depending on the current iteration step.

Specified by:

getMeasurementNoise in interface MeasurementModel

Returns:

the measurement noise matrix

See Also:

KalmanFilter.correct(double[]), KalmanFilter.correct(org.apache.commons.math3.linear.RealVector)