public class ProcessEstimate extends Object
The estimate always contains time, state and covariance. These data are the only ones needed to start a Kalman filter. Once a filter has been started and produces new estimates, these new estimates will always contain a state transition matrix and if the measurement has not been ignored, they will also contain measurement Jacobian, innovation covariance and Kalman gain.
| Constructor and Description | 
|---|
| ProcessEstimate(double time,
               RealVector state,
               RealMatrix covariance)Simple constructor. | 
| ProcessEstimate(double time,
               RealVector state,
               RealMatrix covariance,
               RealMatrix stateTransitionMatrix,
               RealMatrix measurementJacobian,
               RealMatrix innovationCovariance,
               RealMatrix kalmanGain)Simple constructor. | 
| Modifier and Type | Method and Description | 
|---|---|
| RealMatrix | getCovariance()Get the state covariance. | 
| RealMatrix | getInnovationCovariance()Get the innovation covariance matrix. | 
| RealMatrix | getKalmanGain()Get the Kalman gain matrix. | 
| RealMatrix | getMeasurementJacobian()Get the Jacobian of the measurement with respect to the state (H matrix). | 
| RealVector | getState()Get the state vector. | 
| RealMatrix | getStateTransitionMatrix()Get state transition matrix between previous state and estimated (but not yet corrected) state. | 
| double | getTime()Get the process time. | 
public ProcessEstimate(double time,
                       RealVector state,
                       RealMatrix covariance)
This constructor sets state transition matrix, covariance matrix H, innovation covariance matrix and Kalman gain k to null.
time - process time (typically the time or index of a measurement)state - state vectorcovariance - state covariancepublic ProcessEstimate(double time,
                       RealVector state,
                       RealMatrix covariance,
                       RealMatrix stateTransitionMatrix,
                       RealMatrix measurementJacobian,
                       RealMatrix innovationCovariance,
                       RealMatrix kalmanGain)
time - process time (typically the time or index of a measurement)state - state vectorcovariance - state covariancestateTransitionMatrix - state transition matrix between previous state and estimated (but not yet corrected) statemeasurementJacobian - Jacobian of the measurement with respect to the stateinnovationCovariance - innovation covariance matrix, defined as \(h.P.h^T + r\), may be nullkalmanGain - Kalman Gain matrix, may be nullpublic double getTime()
public RealVector getState()
public RealMatrix getCovariance()
public RealMatrix getStateTransitionMatrix()
public RealMatrix getMeasurementJacobian()
public RealMatrix getInnovationCovariance()
public RealMatrix getKalmanGain()
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