User Manual

11.4 Xsens Kalman Filter

The orientation of the MTw is computed by Xsens Kalman Filter for 3 degrees-of-freedom

(3DoF) orientation (XKF-3w). XKF-3w uses signals of the rate gyroscopes, accelerometers and

magnetometers to compute a statistical optimal 3D orientation estimate of high accuracy

with no drift for both static and dynamic movements.

The design of the XKF-3w algorithm can be explained as a sensor fusion algorithm where the

measurement of gravity (by the 3D accelerometers) and Earth magnetic north (by the 3D

magnetometers) compensate for otherwise slowly, but unlimited, increasing (drift) errors

from the integration of rate of turn data (angular velocity from the rate gyros). This type of

drift compensation is often called attitude and heading referenced and such a system is

often called an Attitude and Heading Reference System (AHRS). For the MTw, a specific

Xsens Kalman Filter (XKF-3-w) has been developed to deal with the nature of wireless

transmissions (e.g. irregular updates due to temporal packets losses) and the use of high-

accuracy strap down integration. In-depth documentation/whitepapers will be provided at a

later date. For specific questions, please contact support@xsens.com.

11.4.1 Using the Acceleration of Gravity to Stabilize Inclination (Roll/Pitch)

XKF-3w stabilizes the inclination (i.e. roll and pitch combined, also known as “attitude”)

using the accelerometer signals. An accelerometer measures gravitational acceleration plus

acceleration due to the movement of the object with respect to its surroundings.

XKF-3w uses the assumption that on average the acceleration due to the movement is zero.

Using this assumption, the direction of the gravity can be observed and used to stabilize the

attitude. The orientation of the MT in the gravity field is accounted for so that centripetal

accelerations or asymmetrical movements cannot cause a degraded orientation estimate

performance. This assumption is surprisingly powerful, almost all moving objects undergo

accelerations if they are moving, but in most cases the average acceleration with respect to

the environment during some period of time is zero. The key here is the amount of time over

which the acceleration must be averaged for the assumption to hold. During this time, the

rate gyroscopes must be able to track the orientation to a high degree of accuracy. In

practice, this limits the amount of time over which the assumption holds true. For the class

of miniature MEMS rate gyroscopes used in the MT this period of time is about 10-20

seconds maximum.

However, for some applications this assumption does not hold. For example an accelerating

automobile may generate significant accelerations for time periods lasting longer than the

maximum time the MT’s rate gyroscopes can reliably keep track of the orientation. This will

severely degrade the accuracy of the orientation estimates with XKF-3, because the use

scenario (application) does not match the assumptions made. Note however, that as soon as

the movement does again match the assumptions made, XKF-3w will recover and stabilize.

The recovery to optimal accuracy can take some time.