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The MCvKalman type exposes the following members.

Methods

  NameDescription
Public methodEquals
Indicates whether this instance and a specified object are equal.
(Inherited from ValueType.)
Protected methodFinalize
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Returns the hash code for this instance.
(Inherited from ValueType.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns the fully qualified type name of this instance.
(Inherited from ValueType.)

Fields

  NameDescription
Public fieldcontrol_matrix
control matrix (B) (it is not used if there is no control)
Public fieldCP
number of control vector dimensions
Public fieldDP
number of state vector dimensions
Public fieldDynamMatr
=transition_matrix->data.fl
Public fielderror_cov_post
posteriori error estimate covariance matrix P(k)=(I-K(k)*H)*P'(k)
Public fielderror_cov_pre
priori error estimate covariance matrix P'(k)=A*P(k-1)*At + Q)
Public fieldgain
Kalman gain matrix (K(k)): K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R)
Public fieldKalmGainMatr
=gain->data.fl
Public fieldmeasurement_matrix
measurement matrix (H)
Public fieldmeasurement_noise_cov
measurement noise covariance matrix (R)
Public fieldMeasurementMatr
=measurement_matrix->data.fl
Public fieldMNCovariance
=measurement_noise_cov->data.fl
Public fieldMP
number of measurement vector dimensions
Public fieldPNCovariance
=process_noise_cov->data.fl
Public fieldPosterErrorCovariance
=error_cov_post->data.fl
Public fieldPosterState
=state_pre->data.fl
Public fieldPriorErrorCovariance
=error_cov_pre->data.fl
Public fieldPriorState
=state_post->data.fl
Public fieldprocess_noise_cov
process noise covariance matrix (Q)
Public fieldstate_post
corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k))
Public fieldstate_pre
predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k)
Public fieldtemp1
temporary matrices
Public fieldTemp1Data
temp1->data.fl
Public fieldtemp2
temporary matrices
Public fieldTemp2Data
temp2->data.fl
Public fieldtemp3
temporary matrices
Public fieldtemp4
temporary matrices
Public fieldtemp5
temporary matrices
Public fieldtransition_matrix
state transition matrix (A)

See Also