KalmanGyroscopePredictor

class KalmanGyroscopePredictor(phiMatrixMethod: PhiMatrixMethod = PhiMatrixMethod.APPROXIMATED, processNoiseCovarianceMethod: ProcessNoiseCovarianceMethod = ProcessNoiseCovarianceMethod.BETTER, quaternionStepIntegratorType: QuaternionStepIntegratorType = QuaternionStepIntegratorType.RUNGE_KUTTA, val gyroscopeNoisePsd: Double = DEFAULT_GYROSCOPE_NOISE_PSD)

Predicts next Kalman filter state based on current gyroscope measurement.

Parameters

phiMatrixMethod

method to estimate phi matrix relating previous and current filter state.

processNoiseCovarianceMethod

method to estimate process noise covariance matrix.

quaternionStepIntegratorType

method to integrate quaternions on each measurement.

Constructors

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constructor(phiMatrixMethod: PhiMatrixMethod = PhiMatrixMethod.APPROXIMATED, processNoiseCovarianceMethod: ProcessNoiseCovarianceMethod = ProcessNoiseCovarianceMethod.BETTER, quaternionStepIntegratorType: QuaternionStepIntegratorType = QuaternionStepIntegratorType.RUNGE_KUTTA, gyroscopeNoisePsd: Double = DEFAULT_GYROSCOPE_NOISE_PSD)

Types

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object Companion

Properties

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gyroscope noise PSD.

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Kalman filter error covariance matrix after prediction.

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Kalman filter error covariance matrix before prediction.

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Kalman filter state after prediction.

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Kalman filter state before prediction.

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var nedBodyAngularSpeedTriad: AngularSpeedTriad

Contains gyroscope data expressed in NED coordinates respect to body.

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val predictedBodyQ: Quaternion

Contains predicted attitude respect to body for next step. Because rotation is defined respect to body, rotation converts from body coordinates to leveled local NED coordinates respect to Earth: pn = previousBodyQ * pb

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var previousBodyQ: Quaternion

Previous step attitude respect to body. Because rotation is defined respect to body, rotation converts from body coordinates to leveled local NED coordinates respect to Earth: pn = previousBodyQ * pb

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val q: Matrix

Continuous time process noise covariance matrix.

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val qba: Matrix

Covariance noise matrix of the accelerometer bias

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val qbg: Matrix

Covariance noise matrix of the gyroscope bias

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val rg: Matrix

Covariance measurement matrix of the gyroscope measurements.

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Time interval between measurements expressed in seconds (s).

Functions

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fun predict()

Predicts expected orientation, orientation error, gyroscope and accelerometer biases using current gyroscope measurements and current orientation estimation.

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fun reset()

Resets internal parameter.