- move EV yaw and EV position to new state machines
- EV yaw and EV pos now configured via EKF2_EV_CTRL (migrated from EKF2_AID_MASK)
- new EV position offset estimator to enable EV position while GPS position is active (no more EV pos delta fusion)
- yaw_align now strictly means north (no more rotate external vision aid mask)
- automatic switching between EV yaw, and yaw align north based on GPS quality
Also remove the legacy "range aid" than can be achieved by setting the
height reference to range finder and the range finder control parameter
to "conditional".
Conditional range aiding cal also be set when the height reference isn't
the range finder. This prevents the ratchetting effect due to switching
between references.
Instead of having a single height source fused into the EKF and the
other ones "waiting" for a failure or the primary sensor, fuse all
sources in EKF2 at the same time. To prevent the sources from fighting against each
other, the "primary" source is set as reference and the other ones are
running a bias estimator in order to make all the secondary height
sources converge to the primary one.
If the reference isn't available, another one is automatically selected
from a priority list. This secondary reference keeps its current bias
estimate but stops updating it in order to be the new reference as close
as possible to the primary one.
The noise spectral density, NSD, (square root of power spectral density) is a
continuous-time parameter that makes the tuning independent from the EKF
prediction rate.
NSD corresponds to the rate at which the state uncertainty increases
when no measurements are fused into the filter.
Given that the current prediction rate of EKF2 is 100Hz, the
same tuning is obtained by dividing the std_dev legacy parameter by 10:
nsd = sqrt(std_dev^2 / 100Hz)
- move vehicle at reset detection ekf2 -> land_detector
- ekf_unit: reduce init period
- Fake fusion is when at rest is quite strong and makes the variance reduce rapidly. Reduce the amount of time we wait before checking if the variances are still large enough.
- ekf_unit: reduce minimum vel/pos variance required after init
- Fake pos fusion has a low observation noise, making the vel/pos variances reduce quickly.
Co-authored-by:: bresch <brescianimathieu@gmail.com>
- introduces new parameter EKF2_PREDICT_US to configure the filter
update period in microseconds
- actual filter update period will be an integer multiple of IMU
- this is to help more users get the benefit (by default) and perhaps circumvent the common mistake of setting EKF2_HGT_MODE to range sensor
- this should be safe to enable as the range aid defaults are fairly conservative (max horizontal velocity 1 m/s, and range aid gate 1 SD)
- handle saving the mag bias per sensor (across all estimator instances using that mag) in sensors/vehicle_magnetometer
- this is now saving back to the actual mag calibration CAL_MAGn_OFF{X,Y,Z}
- ekf2 reset mag mag bias on any magnetometer or calibration change
- use Kalman filter scheme to update stored mag bias parameters using all available bias estimates for that sensor
Co-authored-by: Paul Riseborough <gncsolns@gmail.com>
- ekf2 can now run in multi-instance mode (currently up to 9 instances)
- in multi mode all estimates are published to alternate topics (eg estimator_attitude instead of vehicle_attitude)
- new ekf2 selector runs in multi-instance mode to monitor and compare all instances, selecting a primary (eg N x estimator_attitude => vehicle_attitude)
- sensors module accel & gyro inconsistency checks are now relative to the mean of all instances, rather than the current primary (when active ekf2 selector is responsible for choosing primary accel & gyro)
- existing consumers of estimator_status must check estimator_selector_status to select current primary instance status
- ekf2 single instance mode is still fully supported and the default
Co-authored-by: Paul Riseborough <gncsolns@gmail.com>
- new sensors work item that subscribes to N x sensor_gps and publishes vehicle_gps_position
- blending is now configurable with SENS_GPS_MASK and SENS_GPS_TAU
Co-authored-by: Jacob Crabill <jacob@volans-i.com>
Co-authored-by: Jacob Dahl <dahl.jakejacob@gmail.com>
* msg: Add EKF-GSF yaw estimator logging data
* ecl: update to version with EKF-GSF yaw estimator
* ekf2: Add param control and logging for EKF-GSF yaw estimator
* logger: Add logging for EKF-GSF yaw esimtator
Daniel Agar