Interface NonLinearProcess<T extends Measurement>
-
- Type Parameters:
T- the type of the measurements
public interface NonLinearProcess<T extends Measurement>Non-linear process that can be estimated by aExtendedKalmanFilter.This interface must be implemented by users to represent the behavior of the process to be estimated
- Since:
- 1.3
- See Also:
ExtendedKalmanFilter,LinearProcess
-
-
Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description NonLinearEvolutiongetEvolution(double previousTime, RealVector previousState, T measurement)Get the state evolution between two times.RealVectorgetInnovation(T measurement, NonLinearEvolution evolution, RealMatrix innovationCovarianceMatrix)Get the innovation brought by a measurement.
-
-
-
Method Detail
-
getEvolution
NonLinearEvolution getEvolution(double previousTime, RealVector previousState, T measurement)
Get the state evolution between two times.- Parameters:
previousTime- time of the previous statepreviousState- process state atpreviousTimemeasurement- measurement to process- Returns:
- state evolution
-
getInnovation
RealVector getInnovation(T measurement, NonLinearEvolution evolution, RealMatrix innovationCovarianceMatrix)
Get the innovation brought by a measurement.- Parameters:
measurement- measurement to processevolution- evolution returned by a previous call togetEvolution(double, RealVector, Measurement)innovationCovarianceMatrix- innovation covariance matrix, defined as \(h.P.h^T + r\) where h is themeasurement Jacobian, P is the predicted covariance and r ismeasurement covariance- Returns:
- innovation brought by a measurement, may be null if measurement should be rejected
-
-