ahrs.EKF.QUATERNION: EKF-based AHRS algorithm

In RAHRS: Data Fusion Filters for Attitude Heading Reference System (AHRS) with Several Variants of the Kalman Filter and the Mahoney and Madgwick Filters

Description

Implementation of the EKF-based AHRS algorithm based on measurements from three-component accelerometer with orthogonal axes, vector magnetometer and three-axis gyroscope. Estimates the current quaternion attitude.

Usage

ahrs.EKF.QUATERNION(Filter, Sensors, Parameters)

Arguments

Filter	data structure for Extended Kalman Filter
Sensors	calibrated gyroscope, accelerometer and magnetometer measurements 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
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

Value

Q estimated attitude quaternion [1x4] Filter data structure for an Extended Kalman Filter dw estimated gyroscopes bias [1x3]

Author(s)

Jose Gama

References

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

RAHRS documentation built on May 2, 2019, 2:42 a.m.