## 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
Version:
  $Id: DefaultMeasurementModel.java 1416643 2012-12-03 19:37:14Z tn $

Field Summary
`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
`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
`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)`

Copyright (c) 2003-2013 Apache Software Foundation