If state errors were large before the reset, then failure to reset the covariance matrix terms can result in incorrect fusion of position and velocity measurements after the reset due to inconsistencies in the covariance matrix.
When performing the initial in-flight mag yaw reset for RW vehicle, do not reset the quaternion states and corresponding variances unless there has been a change in yaw angle large enough to cause problems with navigation.
This is because the state estimates after a reset are more vulnerable to transient sensor errors, so a reset should be avoided if possible.
When performing the initial in-flight magnetic field reset for fixed wing vehicles, resetting the quaternion states and their corresponding covariances should be avoided unless yaw errors are large, because state estimates are vulnerable to transient sensor errors immediately following a reset.
Ensures that a complete reset of velocity and position states will always be performed if yaw has had to be reset using GPS velocity.
Ensures that the yaw_align status cannot be set to false once the filter has aligned.
Fuse external vision data using a relative position odometry method when GPS data is also being used and enable both GPOS and EV data to be fused on the same time step.
Use horizontal acceleration to check if yaw is observable independent of the magnetometer.
Use rotation about the vertical to check if mag raises are observable.
If neither yaw of mag biases are observable, save the magnetic field variances and switch to magnetic yaw fusion.
Use the last learned declination when using magnetic yaw fusion so that the yaw reference remains consistent.
When yaw or biases become observable, reinstate the saved variances and switch back to 3D mag fusion.
Add a bitmask parameter to control bias learning for individual axes. This is achieved by setting the disabled states to zero together with their corresponding covariances.
Minor cleanup of the covariance prediction comments.
Removal of unnecessary variable copy operations.
Replace index operations to initialise covariance to zero with the more efficient memset.
This change removes the following compiler error when building using the ARM cross compiler.
/Users/paul/src/Firmware/src/lib/ecl/EKF/ekf_helper.cpp:45:12: error: 'std::abs' has not been declared
using std::abs;
This was incorrectly using the IMU (1/250 sec) timestamp instead of the EKF (1/100 sec) value.
The corresponding accelerometer limit has been made a parameter and adjusted to match previous behaviour.
Paul Riseborough