Interface NonLinearProcess<T extends Measurement>
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- 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
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Method Summary
All Methods Instance Methods Abstract Methods 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.
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Method Detail
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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 atpreviousTime
measurement
- measurement to process- Returns:
- state evolution
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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
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