* ekf: disable xy accel bias learning before takeoff
As those biases are usually poorly observable before takeoff because
they are almost perpendicular to the gravity vector, learning is often
driven by noise and numerical issues. This results in incorrect bias
learning before takeoff when the drone is static on ground for a long
period of time.
* ekf: update unit test and change indicator
* EKF: Improve covariance prediction stability
Eliminates collapse of vertical velocity state variance due to rounding errors that can occur under some operating conditions.
* EKF: Fix typo
* test: Fix initialisation test cases
Provide sufficient time for variances to stabilise and fix calculation of reference quaternion for alignment.
* test: Allow for accumulated rounding error in IMU sampling test
* test: Allow sufficient time for quaternion variances to reduce after initial alignment
* test: Increase allowance for tilt alignment delay and inertial nav errors
* test: Increase allowance for tilt alignment delay and inertial nav errors
* adpat reset velocity test
* test: update change indication file
* test: Adjust tests to handle alignment time and prediction errors
* README.md: Add documentation for change indicator test
* EKF: do not fuse multiple times the same height
The _fuse_height flag was never set to zero, hence the fusion was called
at each iteration, even if no new data is available.
The effects were: high CPU usage and virtually less measurement noise
due to multiple fusion of the same sample
Also remve unused variables
* Add primitive logging for Ekf
* Add python script to extract sensor data from ULog
* Add primitive sensor replay
* Add iris_gps data for sensor replay
* Add CI for functional change indication
* Update sensor replay flow data type
* update iris_gps_change indication
* test: Update EKF replay test documentation
Co-authored-by: Paul Riseborough <priseborough@users.noreply.github.com>
bresch