Package org.orekit.estimation.measurements.modifiers

Class DynamicOutlierFilter<T extends ObservedMeasurement<T>>

java.lang.Object

org.orekit.estimation.measurements.modifiers.OutlierFilter<T>

org.orekit.estimation.measurements.modifiers.DynamicOutlierFilter<T>

Type Parameters:

T - the type of the measurement

All Implemented Interfaces:

EstimationModifier<T>, ParameterDriversProvider

public class DynamicOutlierFilter<T extends ObservedMeasurement<T>>
extends OutlierFilter<T>

Modifier that sets estimated measurement weight to 0 if residual is too far from expected domain. The "dynamic" aspect comes from the fact that the value of sigma can be changed on demand. This is mainly used when searching for outliers in Kalman filters' prediction phase. The value of sigma is then set to the square root of the diagonal of the matrix (H.Ppred.Ht+R) Note that in the case of the Kalman filter we use the "iteration" word to represent the number of measurements processed by the filter so far.

Since:

9.2

Author:

Luc Maisonobe

Constructor Summary

Constructors

Constructor	Description
DynamicOutlierFilter(int warmup, double maxSigma)	Simple constructor.

Method Summary

Modifier and Type	Method	Description
double[]	getSigma()	Get the current value of sigma.
void	modify(EstimatedMeasurement<T> estimated)	Apply a modifier to an estimated measurement.
void	setSigma(double[] sigma)	Set the current value of sigma.

Methods inherited from class org.orekit.estimation.measurements.modifiers.OutlierFilter

getMaxSigma, getParametersDrivers, getWarmup, modifyWithoutDerivatives

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.orekit.utils.ParameterDriversProvider

getNbParametersDriversValue, getParameterDriver, getParameters, getParameters, getParameters, getParameters, getParametersAllValues, getParametersAllValues, isSupported

Constructor Detail

DynamicOutlierFilter

public DynamicOutlierFilter(int warmup,
                            double maxSigma)

Simple constructor.

Parameters:

warmup - number of iterations before with filter is not applied

maxSigma - detection limit for outlier

Method Detail

getSigma

public double[] getSigma()

Get the current value of sigma.

Returns:

The current value of sigma

setSigma

public void setSigma(double[] sigma)

Set the current value of sigma.

Parameters:

sigma - The value of sigma to set

modify

public void modify(EstimatedMeasurement<T> estimated)

Apply a modifier to an estimated measurement.

Parameters:

estimated - estimated measurement to modify