OutlierFilter.java
/* Copyright 2002-2024 CS GROUP
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* CS licenses this file to You under the Apache License, Version 2.0
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*
* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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package org.orekit.estimation.measurements.modifiers;
import java.util.Collections;
import java.util.List;
import org.hipparchus.util.FastMath;
import org.orekit.estimation.measurements.EstimatedMeasurement;
import org.orekit.estimation.measurements.EstimatedMeasurementBase;
import org.orekit.estimation.measurements.EstimationModifier;
import org.orekit.estimation.measurements.ObservedMeasurement;
import org.orekit.utils.ParameterDriver;
/** Modifier that sets estimated measurement weight to 0 if residual is too far from expected domain.
* @param <T> the type of the measurement
* @author Luc Maisonobe
* @since 8.0
*/
public class OutlierFilter<T extends ObservedMeasurement<T>> implements EstimationModifier<T> {
/** Warmup iterations. */
private final int warmup;
/** Outlier detection limit. */
private final double maxSigma;
/** Simple constructor.
* @param warmup number of iterations before with filter is not applied
* @param maxSigma detection limit for outliers.
*/
public OutlierFilter(final int warmup, final double maxSigma) {
this.warmup = warmup;
this.maxSigma = maxSigma;
}
/** Get the value of warmup iterations.
* @return the value of warmup iterations
*/
protected int getWarmup() {
return warmup;
}
/** Get the value of the outlier detection limit.
* @return the value of the outlier detection limit
*/
protected double getMaxSigma() {
return maxSigma;
}
/** {@inheritDoc} */
@Override
public List<ParameterDriver> getParametersDrivers() {
return Collections.emptyList();
}
/** {@inheritDoc} */
@Override
public void modifyWithoutDerivatives(final EstimatedMeasurementBase<T> estimated) {
if (estimated.getIteration() > warmup) {
// check if observed value is far to estimation
final double[] observed = estimated.getObservedMeasurement().getObservedValue();
final double[] theoretical = estimated.getEstimatedValue();
final double[] sigma = estimated.getObservedMeasurement().getTheoreticalStandardDeviation();
for (int i = 0; i < observed.length; ++i) {
if (FastMath.abs(observed[i] - theoretical[i]) > maxSigma * sigma[i]) {
// observed value is too far, reject measurement
estimated.setStatus(EstimatedMeasurement.Status.REJECTED);
}
}
}
}
}