public class KalmanEstimator extends AbstractKalmanEstimator
The filter uses a OrbitDeterminationPropagatorBuilder
to initialize its reference trajectory NumericalPropagator
or DSSTPropagator
.
The estimated parameters are driven by ParameterDriver
objects. They are of 3 different types:
The total number of estimated parameters is m, the size of the state vector.
The Kalman filter implementation used is provided by the underlying mathematical library Hipparchus. All the variables seen by Hipparchus (states, covariances, measurement matrices...) are normalized using a specific scale for each estimated parameters or standard deviation noise for each measurement components.
A KalmanEstimator
object is built using the build
method of a KalmanEstimatorBuilder
.
Modifier and Type | Method and Description |
---|---|
Propagator[] |
estimationStep(ObservedMeasurement<?> observedMeasurement)
Process a single measurement.
|
protected KalmanEstimation |
getKalmanEstimation()
Get the provider for kalman filter estimations.
|
Propagator[] |
processMeasurements(Iterable<ObservedMeasurement<?>> observedMeasurements)
Process several measurements.
|
void |
setObserver(KalmanObserver observer)
Set the observer.
|
getCurrentDate, getCurrentMeasurementNumber, getEstimatedMeasurementsParameters, getOrbitalParametersDrivers, getPhysicalEstimatedCovarianceMatrix, getPhysicalEstimatedState, getPropagationParametersDrivers
protected KalmanEstimation getKalmanEstimation()
getKalmanEstimation
in class AbstractKalmanEstimator
public void setObserver(KalmanObserver observer)
observer
- the observerpublic Propagator[] estimationStep(ObservedMeasurement<?> observedMeasurement)
Update the filter with the new measurement by calling the estimate method.
observedMeasurement
- the measurement to processpublic Propagator[] processMeasurements(Iterable<ObservedMeasurement<?>> observedMeasurements)
observedMeasurements
- the measurements to process in chronologically sorted orderCopyright © 2002-2023 CS GROUP. All rights reserved.