Attitude quaternion estimation by means of complementary Kalman filter.

1 | ```
ahrs.LKF.VMATCH(Filter, Sensors, q, Parameters)
``` |

`Filter` |
data structure for Linear Kalman Filter Filter.x State vector [3x1] Filter.P Covariance matrix [3x3] Filter.Q System noise matrix [3x3] Filter.R Measurement noise matrix [6x6] |

`Sensors` |
sensors data structure Sensors.w current calibrated gyroscope measurement [3x1], rad/sec Sensors.a current calibrated accelerometer measurement [3x1], g Sensors.m current calibrated magnetometer measurement [3x1], |m| = 1 |

`q` |
quaternion |

`Parameters` |
AHRS Parameters Parameters.mn Magnetic Field Vector In Navigation Frame [3x1], |m| = 1 Parameters.an Acceleration vector In Navigation Frame [3x1], g Parameters.dt Sampling period, 1/Hz |

`Filter` |
data structure for Linear Kalman Filter |

`Q` |
Correct quaternion |

Jose Gama

Vlad Maximov, 2012 Scalar Calibration of Vector accelerometers and magnetometers, GyroLib documentation

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