Package com.irurueta.navigation.inertial.calibration.accelerometer

Class PROMedSRobustKnownFrameAccelerometerCalibrator

java.lang.Object

com.irurueta.navigation.inertial.calibration.accelerometer.RobustKnownFrameAccelerometerCalibrator

com.irurueta.navigation.inertial.calibration.accelerometer.PROMedSRobustKnownFrameAccelerometerCalibrator

All Implemented Interfaces:

AccelerometerCalibrator, AccelerometerNonLinearCalibrator, OrderedStandardDeviationFrameBodyKinematicsAccelerometerCalibrator, QualityScoredAccelerometerCalibrator, UnknownBiasAccelerometerCalibrator, UnknownBiasNonLinearAccelerometerCalibrator, AccelerometerBiasUncertaintySource, AccelerometerCalibrationSource

public class PROMedSRobustKnownFrameAccelerometerCalibrator
extends RobustKnownFrameAccelerometerCalibrator

Robustly estimates accelerometer biases, cross couplings and scaling factors using an PROMedS algorithm to discard outliers.

To use this calibrator at least 4 measurements at different known frames must be provided. In other words, accelerometer samples must be obtained at 4 different positions, orientations and velocities (although typically velocities are always zero).

Measured specific force is assumed to follow the model shown below:

     fmeas = ba + (I + Ma) * ftrue + w
 

Where: - fmeas is the measured specific force. This is a 3x1 vector. - ba is accelerometer bias. Ideally, on a perfect accelerometer, this should be a 3x1 zero vector. - I is the 3x3 identity matrix. - Ma is the 3x3 matrix containing cross-couplings and scaling factors. Ideally, on a perfect accelerometer, this should be a 3x3 zero matrix. - ftrue is ground-truth specific force. - w is measurement noise.

Nested Class Summary

Nested classes/interfaces inherited from class com.irurueta.navigation.inertial.calibration.accelerometer.RobustKnownFrameAccelerometerCalibrator

RobustKnownFrameAccelerometerCalibrator.PreliminaryResult

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[]	qualityScores	Quality scores corresponding to each provided sample.
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.accelerometer.RobustKnownFrameAccelerometerCalibrator

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
PROMedSRobustKnownFrameAccelerometerCalibrator()	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(boolean commonAxisUsed)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(boolean commonAxisUsed, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, boolean commonAxisUsed)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, boolean commonAxisUsed, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.
PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements, RobustKnownFrameAccelerometerCalibratorListener listener)	Constructor.

Method Summary

Modifier and Type	Method	Description
void	calibrate()	Estimates accelerometer calibration parameters containing bias, scale factors and cross-coupling errors.
com.irurueta.numerical.robust.RobustEstimatorMethod	getMethod()	Returns method being used for robust estimation.
double[]	getQualityScores()	Returns quality scores corresponding to each provided sample.
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.
private void	internalSetQualityScores(double[] qualityScores)	Sets quality scores corresponding to each provided sample.
boolean	isQualityScoresRequired()	Indicates whether this calibrator requires quality scores for each measurement or not.
boolean	isReady()	Indicates whether solver is ready to find a solution.
void	setQualityScores(double[] qualityScores)	Sets quality scores corresponding to each provided sample.
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.accelerometer.RobustKnownFrameAccelerometerCalibrator

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, create, create, create, create, create, create, create, create, getConfidence, getEstimatedBiasAsTriad, getEstimatedBiasAsTriad, getEstimatedBiases, getEstimatedBiases, getEstimatedBiasesAsMatrix, getEstimatedBiasesAsMatrix, getEstimatedBiasFx, getEstimatedBiasFxAsAcceleration, getEstimatedBiasFxAsAcceleration, getEstimatedBiasFxStandardDeviation, getEstimatedBiasFxStandardDeviationAsAcceleration, getEstimatedBiasFxStandardDeviationAsAcceleration, getEstimatedBiasFxVariance, getEstimatedBiasFy, getEstimatedBiasFyAsAcceleration, getEstimatedBiasFyAsAcceleration, getEstimatedBiasFyStandardDeviation, getEstimatedBiasFyStandardDeviationAsAcceleration, getEstimatedBiasFyStandardDeviationAsAcceleration, getEstimatedBiasFyVariance, getEstimatedBiasFz, getEstimatedBiasFzAsAcceleration, getEstimatedBiasFzAsAcceleration, getEstimatedBiasFzStandardDeviation, getEstimatedBiasFzStandardDeviationAsAcceleration, getEstimatedBiasFzStandardDeviationAsAcceleration, getEstimatedBiasFzVariance, getEstimatedBiasStandardDeviation, getEstimatedBiasStandardDeviation, getEstimatedBiasStandardDeviationAverage, getEstimatedBiasStandardDeviationAverageAsAcceleration, getEstimatedBiasStandardDeviationAverageAsAcceleration, getEstimatedBiasStandardDeviationNorm, getEstimatedBiasStandardDeviationNormAsAcceleration, getEstimatedBiasStandardDeviationNormAsAcceleration, getEstimatedChiSq, getEstimatedCovariance, getEstimatedMa, getEstimatedMse, getEstimatedMxy, getEstimatedMxz, getEstimatedMyx, getEstimatedMyz, getEstimatedMzx, getEstimatedMzy, getEstimatedSx, getEstimatedSy, getEstimatedSz, getInitialBias, getInitialBias, getInitialBiasAsMatrix, getInitialBiasAsMatrix, getInitialBiasAsTriad, getInitialBiasAsTriad, getInitialBiasX, getInitialBiasXAsAcceleration, getInitialBiasXAsAcceleration, getInitialBiasY, getInitialBiasYAsAcceleration, getInitialBiasYAsAcceleration, getInitialBiasZ, getInitialBiasZAsAcceleration, getInitialBiasZAsAcceleration, getInitialMa, getInitialMa, getInitialMxy, getInitialMxz, getInitialMyx, getInitialMyz, getInitialMzx, getInitialMzy, getInitialSx, getInitialSy, getInitialSz, getInliersData, getListener, getMaxIterations, getMeasurements, getMeasurementType, getMinimumRequiredMeasurements, getPreliminarySubsetSize, getProgressDelta, isCommonAxisUsed, isCovarianceKept, isLinearCalibratorUsed, isOrderedMeasurementsRequired, isPreliminarySolutionRefined, isResultRefined, isRunning, setCommonAxisUsed, setConfidence, setCovarianceKept, setInitialBias, setInitialBias, setInitialBias, setInitialBias, setInitialBias, setInitialBiasX, setInitialBiasX, setInitialBiasY, setInitialBiasY, setInitialBiasZ, setInitialBiasZ, setInitialCrossCouplingErrors, setInitialMa, setInitialMxy, setInitialMxz, setInitialMyx, setInitialMyz, setInitialMzx, setInitialMzy, setInitialScalingFactors, setInitialScalingFactorsAndCrossCouplingErrors, setInitialSx, setInitialSy, setInitialSz, setLinearCalibratorUsed, setListener, setMaxIterations, setMeasurements, setPreliminarySolutionRefined, setPreliminarySubsetSize, setProgressDelta, setResultRefined

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

qualityScores

private double[] qualityScores

Quality scores corresponding to each provided sample. The larger the score value the better the quality of the sample.

Constructor Details

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator()

Constructor.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

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

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements)

Constructor.

Parameters:

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

listener - listener to handle events raised by this calibrator.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(boolean commonAxisUsed)

Constructor.

Parameters:

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

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(boolean commonAxisUsed,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

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

listener - listener to handle events raised by this calibrator.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements,
 boolean commonAxisUsed)

Constructor.

Parameters:

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

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

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(List<StandardDeviationFrameBodyKinematics> measurements,
 boolean commonAxisUsed,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

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

listener - listener to handle events raised by this calibrator.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

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

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 List<StandardDeviationFrameBodyKinematics> measurements)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 List<StandardDeviationFrameBodyKinematics> measurements,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

listener - listener to handle events raised by this calibrator.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 boolean commonAxisUsed)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

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

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 boolean commonAxisUsed,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

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

listener - listener to handle events raised by this calibrator.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 List<StandardDeviationFrameBodyKinematics> measurements,
 boolean commonAxisUsed)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

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

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

PROMedSRobustKnownFrameAccelerometerCalibrator

public PROMedSRobustKnownFrameAccelerometerCalibrator(double[] qualityScores,
 List<StandardDeviationFrameBodyKinematics> measurements,
 boolean commonAxisUsed,
 RobustKnownFrameAccelerometerCalibratorListener listener)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.

measurements - list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).

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

listener - listener to handle events raised by this calibrator.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 4 samples.

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.

getQualityScores

public double[] getQualityScores()

Returns quality scores corresponding to each provided sample. The larger the score value the better the quality of the sample.

Specified by:

getQualityScores in interface QualityScoredAccelerometerCalibrator

Overrides:

getQualityScores in class RobustKnownFrameAccelerometerCalibrator

Returns:

quality scores corresponding to each sample.

setQualityScores

public void setQualityScores(double[] qualityScores)
                      throws com.irurueta.navigation.LockedException

Sets quality scores corresponding to each provided sample. The larger the score value the better the quality of the sample.

Specified by:

setQualityScores in interface QualityScoredAccelerometerCalibrator

Overrides:

setQualityScores in class RobustKnownFrameAccelerometerCalibrator

Parameters:

qualityScores - quality scores corresponding to each sample.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than minimum required samples.

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

isReady

public boolean isReady()

Indicates whether solver is ready to find a solution.

Specified by:

isReady in interface AccelerometerCalibrator

Overrides:

isReady in class RobustKnownFrameAccelerometerCalibrator

Returns:

true if solver is ready, false otherwise.

calibrate

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

Estimates accelerometer calibration parameters containing bias, 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 RobustKnownFrameAccelerometerCalibrator

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.

internalSetQualityScores

private void internalSetQualityScores(double[] qualityScores)

Sets quality scores corresponding to each provided sample. This method is used internally and does not check whether instance is locked or not.

Parameters:

qualityScores - quality scores to be set.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than 3 samples.