The MCvKalman type exposes the following fields.
Fields
 Public Protected | Instance Static | Declared Inherited | XNA Framework Only .NET Compact Framework Only |
| Member | 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)
|
See Also
