T - the type of the measurementspublic interface NonLinearProcess<T extends Measurement>
ExtendedKalmanFilter.
 This interface must be implemented by users to represent the behavior of the process to be estimated
ExtendedKalmanFilter, 
LinearProcess| Modifier and Type | Method and Description | 
|---|---|
| NonLinearEvolution | getEvolution(double previousTime,
            RealVector previousState,
            T measurement)Get the state evolution between two times. | 
| RealVector | getInnovation(T measurement,
             NonLinearEvolution evolution,
             RealMatrix innovationCovarianceMatrix)Get the innovation brought by a measurement. | 
NonLinearEvolution getEvolution(double previousTime, RealVector previousState, T measurement)
previousTime - time of the previous statepreviousState - process state at previousTimemeasurement - measurement to processRealVector getInnovation(T measurement, NonLinearEvolution evolution, RealMatrix innovationCovarianceMatrix)
measurement - measurement to processevolution - evolution returned by a previous call to getEvolution(double, RealVector, Measurement)innovationCovarianceMatrix - innovation covariance matrix, defined as \(h.P.h^T + r\)
 where h is the measurement Jacobian,
 P is the predicted covariance and r is measurement covarianceCopyright © 2016–2020 Hipparchus.org. All rights reserved.