- when GNSS is used require low mag heading innovations during
horizontal acceleration (yaw observable) to validate the mag
- only fuse mag heading just enough to constrain the yaw estimate
variance to a sane value. Leave enough uncertainty to allow for a
correction when the yaw is observable through GNSS fusion
- split mag_3d into new standalone mag fusion and mag fusion allowed to update all states (full mag_3d)
- new dedicated control logic for mag/mag_3d fusion and standalone mag heading fusion
- if WMM available use for mag_I and mag_B init
- mag states reset if external yaw reset (yaw estimator, GPS yaw, etc)
- mag reset if declination changed (eliminate _mag_yaw_reset_req)
- mag fusion (but not mag_hdg or mag_3d) can be active during gps_yaw or ev_yaw (if yaw aligned north)
Co-authored-by: bresch <brescianimathieu@gmail.com>
* ekf2-test: remove outdated codegen comparison
The definition of states changed so the comparison with the old
derivation cannot work anymore.
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Co-authored-by: bresch <brescianimathieu@gmail.com>
This can be useful if using a full EV + GNSS setup and you start indoors, then fly outside. Once GPS is good and the only missing requirement is yaw alignment the yaw estimator reset is performed and EV yaw will automatically stop itself.
There is no reason to contrsain the position uncertainty, estpecially
when flying with velocitiy aiding only.
Note that all the variances are already contrained to sane values at the
end of the covariance prediction
- set vision attitude error filter uninitialized if vision data stops
- ev error filter is only compiled when ev config is selected
Co-authored-by: bresch <brescianimathieu@gmail.com>
When at rest, directly fuse the gyro data as an observation of its bias.
This allows to strongly observe the gyro biases without having to fuse a
constant heading that makes the ekf too confident about its heading.
Tests showed that sideslip fusion often starts just before airspeed
fusion, resetting the wind states to 0 instead of using the airspeed
data. A quick look at the wind uncertainty allows to know if the current
wind estimate is meaningful or if we should rather reset it using the
airspeed data.