If the magnetometer fails innovation consistency checks for too long (currently 10 sec), then the next available sensor approved for yaw measurement will be used.
The original design intent was to require all axes to pass because severe errors are rarely constrained to a single axis.
This was not achieved with the previous implementation.
These changes move the innovation consistency checks for all three axes to the top before any axes are fused.
Unnecessary performance timers have been removed.
This was problematic to implement with magnetometer switching. It is likely that slow magnetometer learning can still be performed externally (eg plane) but this will need to be monitored to see if it causes issues.
The setting of the EKF origin and the entry into GPS aiding mode have been separated to make the logic clear.
The order of operations has been changed to ensure that when a reset to GPS is performed, a valid GPS measurement is available in the buffer
Declaration of GPS availability is not made unless the GPS data has been entered into the buffer
Only applied to interfaces required for data logging.
If an invalid instance is requested, the data for the primary instance is returned. This allows the primary data to be returned by calling with a -1 instance value.
Apply filtering to baro innovation check and and don't apply innovation checks once aiding has commenced because GPS and baro disturbances on the ground and during launch could generate a false positive
Prevents frame over-runs due to simultaneous fusion of measurements on each instance.
The offset is only applied if less than 5msec available between frames
Vibration in the 400Hz delta angles could cause the angular rate condition check for in-flight magnetic field alignment to fail.
The symptons were failure to start magnetic field learning as expected when EK2_MAG_CAL=3 was set.
Use the more robust, but less accurate compass heading fusion up to 5m altitude
Wait for the magnetometer data fusion time offset to be correct before using data to reset states
Don't reset magnetic field states if the vehicle is rotating rapidly as timing offsets will produce large errors
When doing the yaw angle reset, apply the reset increment to all quaternions stored in the output buffer to avoid transients produced by yaw rotations and the 0.25 second fusion time horizon offset.
Only do the one yaw and mag reset at 5m, not two at 1.5 and 5.0m
Always re-do the yaw and mag reset when leaving the ground.
Now variables don't have to be declared with PROGMEM anymore, so remove
them. This was automated with:
git grep -l -z PROGMEM | xargs -0 sed -i 's/ PROGMEM / /g'
git grep -l -z PROGMEM | xargs -0 sed -i 's/PROGMEM//g'
The 2 commands were done so we don't leave behind spurious spaces.
AVR-specific places were not changed.
The PSTR is already define as a NOP for all supported platforms. It's
only needed for AVR so here we remove all the uses throughout the
codebase.
This was automated with a simple python script so it also converts
places which spans to multiple lines, removing the matching parentheses.
AVR-specific places were not changed.
This increase in assumed altimeter noise and reduction in accel noise has been flight tested by L.Hall with noticeable reduction in the immediate response to Baro errors during moving flight.
This increases the time constant of response to baro errors such that the pilot can more easily compensate.
The previous gain from rate to magnetometer error was excessive. The revised value is equivalent to a magnetic field length of 0.5 with a timing uncertainty of 0.01 sec
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.
The failure to initialise the magnetometer bias states to zero can result in a large jump in yaw gyro bias and heading when a heading reset is performed.
MPU6000 data sheet indicates that variation on gyro ZRO across temperature range from -40 to +85 is +-20 deg/sec.
The limits on the gyro bias states have been increased to allow for this.
To enable the EKF to accommodate such large gyro bias values in yaw without the yaw error wrapping, leading to continual heading drift, an unwrap function has been applied to the compass heading error.
Paul Riseborough
Andrew Tridgell
Lucas De Marchi
Randy Mackay
Siddharth Bharat Purohit
Paul Riseborough