ahrs.LKF.VMATCH

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]


Filter

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


Sensors

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


Parameters


Attitude quaternion estimation by means of complementary
Kalman filter.


 ~Programming 

Data fusion filters for Attitude Heading Reference System (AHRS) based on
Vlad Maximov's GyroLib AHRS library (quaternion based linearized/extended/unscented Kalman filter,
Euler based LKF, gyro-free with vector matching, SVD calibration and EKF calibration),
Sebastian O.H. Madgwick AHRS algorithms and Sebastian O.H. Madgwick implementation of Mayhony et al AHRS algorithm.

ahrs.LKF.VMATCH: Quaternion estimation with vector matching and Kalman filter

Description

Usage

Arguments

Value

References