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 | 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 © 2016–2018 Hipparchus.org. All rights reserved.