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

Class LMedSRobustKnownFrameMagnetometerCalibrator

java.lang.Object
com.irurueta.navigation.inertial.calibration.magnetometer.RobustKnownFrameMagnetometerCalibrator
com.irurueta.navigation.inertial.calibration.magnetometer.LMedSRobustKnownFrameMagnetometerCalibrator
All Implemented Interfaces:
MagnetometerCalibrator, MagnetometerNonLinearCalibrator, OrderedStandardDeviationFrameBodyMagneticFluxDensityMagnetometerCalibrator, QualityScoredMagnetometerCalibrator, UnknownHardIronMagnetometerCalibrator, UnknownHardIronNonLinearMagnetometerCalibrator
public class LMedSRobustKnownFrameMagnetometerCalibrator extends RobustKnownFrameMagnetometerCalibrator
Robustly estimates magnetometer hard-iron biases, 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 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 RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.
      See Also:

    • MIN_STOP_THRESHOLD

      public static final double MIN_STOP_THRESHOLD
      Minimum allowed stop threshold value.
      See Also:

    • 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 RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.

  • Constructor Details

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator()
      Constructor.

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(RobustKnownFrameMagnetometerCalibratorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements)
      Constructor.
      Parameters:
      measurements - list of body magnetic flux density measurements with standard deviations taken at different frames (positions and orientations).

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements, RobustKnownFrameMagnetometerCalibratorListener 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.

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(boolean commonAxisUsed)
      Constructor.
      Parameters:
      commonAxisUsed - indicates whether z-axis is assumed to be common for the accelerometer, gyroscope and magnetometer.

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(boolean commonAxisUsed, RobustKnownFrameMagnetometerCalibratorListener 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.

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(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.

    • LMedSRobustKnownFrameMagnetometerCalibrator

      public LMedSRobustKnownFrameMagnetometerCalibrator(List<StandardDeviationFrameBodyMagneticFluxDensity> measurements, boolean commonAxisUsed, RobustKnownFrameMagnetometerCalibratorListener 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 RANSAC, 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 RANSAC, 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 hard-iron bias and 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 RobustKnownFrameMagnetometerCalibrator
      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.