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The MCvKalman type exposes the following members.
Methods
Name | Description | |
---|---|---|
![]() | Equals |
Indicates whether this instance and a specified object are equal.
(Inherited from ValueType.) |
![]() | Finalize |
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
(Inherited from Object.) |
![]() | GetHashCode |
Returns the hash code for this instance.
(Inherited from ValueType.) |
![]() | GetType |
Gets the Type of the current instance.
(Inherited from Object.) |
![]() | MemberwiseClone |
Creates a shallow copy of the current Object.
(Inherited from Object.) |
![]() | ToString |
Returns the fully qualified type name of this instance.
(Inherited from ValueType.) |
Fields
Name | Description | |
---|---|---|
![]() | control_matrix |
control matrix (B)
(it is not used if there is no control)
|
![]() | CP |
number of control vector dimensions
|
![]() | DP |
number of state vector dimensions
|
![]() | DynamMatr |
=transition_matrix->data.fl
|
![]() | error_cov_post |
posteriori error estimate covariance matrix P(k)=(I-K(k)*H)*P'(k)
|
![]() | error_cov_pre |
priori error estimate covariance matrix P'(k)=A*P(k-1)*At + Q)
|
![]() | gain |
Kalman gain matrix (K(k)):
K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R)
|
![]() | KalmGainMatr |
=gain->data.fl
|
![]() | measurement_matrix |
measurement matrix (H)
|
![]() | measurement_noise_cov |
measurement noise covariance matrix (R)
|
![]() | MeasurementMatr |
=measurement_matrix->data.fl
|
![]() | MNCovariance |
=measurement_noise_cov->data.fl
|
![]() | MP |
number of measurement vector dimensions
|
![]() | PNCovariance |
=process_noise_cov->data.fl
|
![]() | PosterErrorCovariance |
=error_cov_post->data.fl
|
![]() | PosterState |
=state_pre->data.fl
|
![]() | PriorErrorCovariance |
=error_cov_pre->data.fl
|
![]() | PriorState |
=state_post->data.fl
|
![]() | process_noise_cov |
process noise covariance matrix (Q)
|
![]() | state_post |
corrected state (x(k)):
x(k)=x'(k)+K(k)*(z(k)-H*x'(k))
|
![]() | state_pre |
predicted state (x'(k)):
x(k)=A*x(k-1)+B*u(k)
|
![]() | temp1 |
temporary matrices
|
![]() | Temp1Data |
temp1->data.fl
|
![]() | temp2 |
temporary matrices
|
![]() | Temp2Data |
temp2->data.fl
|
![]() | temp3 |
temporary matrices
|
![]() | temp4 |
temporary matrices
|
![]() | temp5 |
temporary matrices
|
![]() | transition_matrix |
state transition matrix (A)
|