Testing on different platforms has shown that the new EKF has smaller innovations enabling innovation consistency checks that reject GPS and baro errors to be tightened.
The position and velocity thresholds for plane have been left the same because planes are less sensitive to GPS glitches as they fly higher and with more separation to surrounding objects. They are also more prone to bad inertial data due to the installation practices.
The altitude noise has been increased on plane to allow for the larger baro disturbances that result from the higher speeds and lack of a proper static pressure source. The innovation consistency gate has been adjusted to provide the same baro error limit of ~20m before baro is rejected.
Extended GPS loss can result in the earth field states becoming rotated and making it difficult for the EKF to recover its heading when GPS is regained.
During prolonged GPS outages, the position covariance can become large enough to cause the reset function to continually activate. This is fixed by ensuring that position covariances are always reset when the position is reset.
The innovation variance was being used incorrectly instead of the state variance to trigger the glitch reset.
Because we have changed the yaw angle and have taken a point sample on the magnetic field, covariances associated with the magnetic field states will be invalid and subsequent innovations could cause an unwanted disturbance in roll and pitch.
The reset of the Euler angles to a new yaw orientation was being done using roll and pitch from the output observer states, not the EKF state vector which meant that when roll and pitch were changing, the reset to a new yaw angle would also cause a roll and pitch disturbance.
This sets the fusion of the synthetic position and velocity to occur at the same time as the barometer
This makes filter tuning more consistent between GPS and non-GPS useage
High measurement data rates can fill buffers with data that is always new and never fused because it is over-written before it falls behind the measurement time horizon.
The legacy EKF switches GPs aiding on on arming, whereas the new EKF switches it on based on GPS data quality.
This means the decision to arm and therefore the predicted solution flags must now reflect the actual status of the navigation solution as it will no longer change when motor arming occurs.
If high vibration levels cause offsets between the two, it switches to the accelerometer with lower vibration levels. The default behaviour is to use the average of both accelerometers.
Don't fuse other measurements on the same frame that magnetometer measurements arrive if running at a high frame rate as there will be insufficient time to complete other operations.
This parameter is a compromise between numerical accuracy of the covariance prediction and sensor timing jitter
Further testing has shown that doing covariance prediction and sensor fusion every 10msec has no observable effect on fusion health and reduces timing hitter noise on magnetometer observations during high rate maneovures
The values chosen ensure that up to consistent 250 msec of sensor delay compensation is available for different platform types
The revised values also ensure that fusion occurs at different time to when the 10Hz magnetometer measurements are read
Adds fusion of the declination when there are no earth relative measurements so that the declination angle and therefore the copters yaw angle have an absolute reference.
This enables the length (but not the declination) of the earth field North/East states to change along with the magnetometer offsets.
Provide an option to always do learning
Make field learning decision logic clearer
Change defaults so that plane learns when airborne
Change defaults so that Rover does not learn (large external magnetic interference)
Magnetic interference whilst on the ground can adversely affect filter states. This patch ensures that the simpler and more robust magnetic heading observation method is used until the vehicle has cleared the ground.
If an external gyro calibration has been performed, we should assume that it has been done under static conditions
Otherwise it is pointless and we should allow the EKF to find its own gyro bias offsets.
Paul Riseborough
Andrew Tridgell