Package com.irurueta.navigation.inertial.calibration.magnetometer

Class LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

java.lang.Object

com.irurueta.navigation.inertial.calibration.magnetometer.RobustKnownHardIronAndFrameMagnetometerCalibrator

com.irurueta.navigation.inertial.calibration.magnetometer.LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

All Implemented Interfaces:

KnownHardIronMagnetometerCalibrator, MagnetometerCalibrator, MagnetometerNonLinearCalibrator, OrderedStandardDeviationFrameBodyMagneticFluxDensityMagnetometerCalibrator, QualityScoredMagnetometerCalibrator

public class LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator
extends RobustKnownHardIronAndFrameMagnetometerCalibrator

Robustly estimates magnetometer soft-iron cross couplings and scaling factors using LMedS algorithm.

To use this calibrator at least 4 measurements at different known frames must be provided. In other words, magnetometer samples must be obtained at 4 different positions or orientations. Notice that frame velocities are ignored by this calibrator.

Measured magnetic flux density is assumed to follow the model shown below:

     mBmeas = bm + (I + Mm) * mBtrue + w
 

Where: - mBmeas is the measured magnetic flux density. This is a 3x1 vector. - bm is magnetometer hard-iron bias. Ideally, on a perfect magnetometer, this should be a 3x1 zero vector. - I is the 3x3 identity matrix. - Mm is the 3x3 soft-iron matrix containing cross-couplings and scaling factors. Ideally, on a perfect magnetometer, this should be a 3x3 zero matrix. - mBtrue is ground-truth magnetic flux density. This is a 3x1 vector. - w is measurement noise. This is a 3x1 vector.

Field Summary

Fields

Modifier and Type	Field	Description
static final double	DEFAULT_STOP_THRESHOLD	Default value to be used for stop threshold.
static final double	MIN_STOP_THRESHOLD	Minimum allowed stop threshold value.
private double	stopThreshold	Threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.

Fields inherited from class com.irurueta.navigation.inertial.calibration.magnetometer.RobustKnownHardIronAndFrameMagnetometerCalibrator

confidence, DEFAULT_CONFIDENCE, DEFAULT_KEEP_COVARIANCE, DEFAULT_MAX_ITERATIONS, DEFAULT_PROGRESS_DELTA, DEFAULT_REFINE_PRELIMINARY_SOLUTIONS, DEFAULT_REFINE_RESULT, DEFAULT_ROBUST_METHOD, DEFAULT_USE_COMMON_Z_AXIS, DEFAULT_USE_LINEAR_CALIBRATOR, inliersData, listener, MAX_CONFIDENCE, MAX_PROGRESS_DELTA, maxIterations, measurements, MIN_CONFIDENCE, MIN_ITERATIONS, MIN_PROGRESS_DELTA, MINIMUM_MEASUREMENTS, preliminarySubsetSize, progressDelta, refineResult, running

Constructor Summary

Constructors

Constructor	Description
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator()	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(boolean commonAxisUsed)	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(boolean commonAxisUsed, RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements)	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements, boolean commonAxisUsed)	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements, boolean commonAxisUsed, RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)	Constructor.
LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements, RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)	Constructor.

Method Summary

Modifier and Type	Method	Description
void	calibrate()	Estimates magnetometer calibration parameters containing soft-iron scale factors and cross-coupling errors.
com.irurueta.numerical.robust.RobustEstimatorMethod	getMethod()	Returns method being used for robust estimation.
double	getStopThreshold()	Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.
boolean	isQualityScoresRequired()	Indicates whether this calibrator requires quality scores for each measurement or not.
void	setStopThreshold(double stopThreshold)	Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.

Methods inherited from class com.irurueta.navigation.inertial.calibration.magnetometer.RobustKnownHardIronAndFrameMagnetometerCalibrator

attemptRefine, computeError, computePreliminarySolutions, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, getConfidence, getEstimatedChiSq, getEstimatedCovariance, getEstimatedMm, getEstimatedMse, getEstimatedMxy, getEstimatedMxz, getEstimatedMyx, getEstimatedMyz, getEstimatedMzx, getEstimatedMzy, getEstimatedSx, getEstimatedSy, getEstimatedSz, getHardIron, getHardIron, getHardIronAsTriad, getHardIronAsTriad, getHardIronMatrix, getHardIronMatrix, getHardIronX, getHardIronXAsMagneticFluxDensity, getHardIronXAsMagneticFluxDensity, getHardIronY, getHardIronYAsMagneticFluxDensity, getHardIronYAsMagneticFluxDensity, getHardIronZ, getHardIronZAsMagneticFluxDensity, getHardIronZAsMagneticFluxDensity, getInitialMm, getInitialMm, getInitialMxy, getInitialMxz, getInitialMyx, getInitialMyz, getInitialMzx, getInitialMzy, getInitialSx, getInitialSy, getInitialSz, getInliersData, getListener, getMagneticModel, getMaxIterations, getMeasurements, getMeasurementType, getMinimumRequiredMeasurements, getPreliminarySubsetSize, getProgressDelta, getQualityScores, isCommonAxisUsed, isCovarianceKept, isLinearCalibratorUsed, isOrderedMeasurementsRequired, isPreliminarySolutionRefined, isReady, isResultRefined, isRunning, setCommonAxisUsed, setConfidence, setCovarianceKept, setHardIron, setHardIron, setHardIron, setHardIronCoordinates, setHardIronCoordinates, setHardIronX, setHardIronX, setHardIronY, setHardIronY, setHardIronZ, setHardIronZ, setInitialCrossCouplingErrors, setInitialMm, setInitialMxy, setInitialMxz, setInitialMyx, setInitialMyz, setInitialMzx, setInitialMzy, setInitialScalingFactors, setInitialScalingFactorsAndCrossCouplingErrors, setInitialSx, setInitialSy, setInitialSz, setLinearCalibratorUsed, setListener, setMagneticModel, setMaxIterations, setMeasurements, setPreliminarySolutionRefined, setPreliminarySubsetSize, setProgressDelta, setQualityScores, setResultRefined, setupWmmEstimator

Methods inherited from class java.lang.Object

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

Field Details

DEFAULT_STOP_THRESHOLD

public static final double DEFAULT_STOP_THRESHOLD

Default value to be used for stop threshold. Stop threshold can be used to avoid keeping the algorithm unnecessarily iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in LMedS, and yet the algorithm could still produce even smaller thresholds in estimated results.

See Also:

• Constant Field Values

MIN_STOP_THRESHOLD

public static final double MIN_STOP_THRESHOLD

Minimum allowed stop threshold value.

See Also:

• Constant Field Values

stopThreshold

private double stopThreshold

Threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in LMedS, and yet the algorithm could still produce even smaller thresholds in estimated results.

Constructor Details

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator()

Constructor.

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)

Constructor.

Parameters:

listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements)

Constructor.

Parameters:

measurements - list of body magnetic flux density measurements with standard deviations taken at different frames (positions and orientations).

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements,
 RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)

Constructor.

Parameters:

measurements - list of body magnetic flux density measurements with standard deviations taken at different frames (positions and orientations).

listener - listener to handle events raised by this calibrator.

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(boolean commonAxisUsed)

Constructor.

Parameters:

commonAxisUsed - indicates whether z-axis is assumed to be common for the accelerometer, gyroscope and magnetometer.

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(boolean commonAxisUsed,
 RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)

Constructor.

Parameters:

commonAxisUsed - indicates whether z-axis is assumed to be common for the accelerometer, gyroscope and magnetometer.

listener - listener to handle events raised by this calibrator.

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements,
 boolean commonAxisUsed)

Constructor.

Parameters:

measurements - list of body magnetic flux density measurements with standard deviations taken at different frames (positions and orientations).

commonAxisUsed - indicates whether z-axis is assumed to be common for the accelerometer, gyroscope and magnetometer.

LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator

public LMedSRobustKnownHardIronAndFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements,
 boolean commonAxisUsed,
 RobustKnownHardIronAndFrameMagnetometerCalibratorListener listener)

Constructor.

Parameters:

measurements - list of body magnetic flux density measurements with standard deviations taken at different frames (positions and orientations).

commonAxisUsed - indicates whether z-axis is assumed to be common for the accelerometer, gyroscope and magnetometer.

listener - listener to handle events raised by this calibrator.

Method Details

getStopThreshold

public double getStopThreshold()

Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm to iterate too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in LMedS, and yet the algorithm could still produce even smaller thresholds in estimated results.

Returns:

stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.

setStopThreshold

public void setStopThreshold(double stopThreshold)
                      throws com.irurueta.navigation.LockedException

Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm to iterate too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in LMedS, and yet the algorithm could still produce even smaller thresholds in estimated results.

Parameters:

stopThreshold - stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.

Throws:

IllegalArgumentException - if provided value is zero or negative.

com.irurueta.navigation.LockedException - if calibrator is currently running.

calibrate

public void calibrate()
               throws com.irurueta.navigation.LockedException,
com.irurueta.navigation.NotReadyException,
CalibrationException

Estimates magnetometer calibration parameters containing soft-iron scale factors and cross-coupling errors.

Throws:

com.irurueta.navigation.LockedException - if calibrator is currently running.

com.irurueta.navigation.NotReadyException - if calibrator is not ready.

CalibrationException - if estimation fails for numerical reasons.

getMethod

public com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()

Returns method being used for robust estimation.

Specified by:

getMethod in class RobustKnownHardIronAndFrameMagnetometerCalibrator

Returns:

method being used for robust estimation.

isQualityScoresRequired

public boolean isQualityScoresRequired()

Indicates whether this calibrator requires quality scores for each measurement or not.

Returns:

true if quality scores are required, false otherwise.