Constructor Detail

• DefaultProcessModel

  public DefaultProcessModel(double[][] stateTransition,
                     double[][] control,
                     double[][] processNoise,
                     double[] initialStateEstimate,
                     double[][] initialErrorCovariance)
                      throws NullArgumentException,
                             NoDataException,
                             DimensionMismatchException

  Create a new ProcessModel, taking double arrays as input parameters.

  Parameters:

  stateTransition - the state transition matrix

  control - the control matrix

  processNoise - the process noise matrix

  initialStateEstimate - the initial state estimate vector

  initialErrorCovariance - the initial error covariance matrix

  Throws:

  NullArgumentException - if any of the input arrays is null

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

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

• DefaultProcessModel

  public DefaultProcessModel(double[][] stateTransition,
                     double[][] control,
                     double[][] processNoise)
                      throws NullArgumentException,
                             NoDataException,
                             DimensionMismatchException

  Create a new ProcessModel, taking double arrays as input parameters.

  The initial state estimate and error covariance are omitted and will be initialized by the KalmanFilter to default values.

  Parameters:

  stateTransition - the state transition matrix

  control - the control matrix

  processNoise - the process noise matrix

  Throws:

  NullArgumentException - if any of the input arrays is null

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

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

• DefaultProcessModel

  public DefaultProcessModel(RealMatrix stateTransition,
                     RealMatrix control,
                     RealMatrix processNoise,
                     RealVector initialStateEstimate,
                     RealMatrix initialErrorCovariance)

  Create a new ProcessModel, taking double arrays as input parameters.

  Parameters:

  stateTransition - the state transition matrix

  control - the control matrix

  processNoise - the process noise matrix

  initialStateEstimate - the initial state estimate vector

  initialErrorCovariance - the initial error covariance matrix

Method Detail

• getStateTransitionMatrix

  public RealMatrix getStateTransitionMatrix()

  Returns the state transition matrix.

  Specified by:

  getStateTransitionMatrix in interface ProcessModel

  Returns:

  the state transition matrix

• getControlMatrix

  public RealMatrix getControlMatrix()

  Returns the control matrix.

  Specified by:

  getControlMatrix in interface ProcessModel

  Returns:

  the control matrix

• getProcessNoise

  public RealMatrix getProcessNoise()

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

  Specified by:

  getProcessNoise in interface ProcessModel

  Returns:

  the process noise matrix

  See Also:

  KalmanFilter.predict(), KalmanFilter.predict(double[]), KalmanFilter.predict(RealVector)

• getInitialStateEstimate

  public RealVector getInitialStateEstimate()

  Returns the initial state estimation vector.

  Note: if the return value is zero, the Kalman filter will initialize the state estimation with a zero vector.

  Specified by:

  getInitialStateEstimate in interface ProcessModel

  Returns:

  the initial state estimation vector

• getInitialErrorCovariance

  public RealMatrix getInitialErrorCovariance()

  Returns the initial error covariance matrix.

  Note: if the return value is zero, the Kalman filter will initialize the error covariance with the process noise matrix.

  Specified by:

  getInitialErrorCovariance in interface ProcessModel

  Returns:

  the initial error covariance matrix