If the GPS receiver was disconnected and no data received, then then the gpsGoodToAlign check did not get a chance to run and becasue it was previously true the EKF would switch back into aiding.
This prevents this by ensuring that gpsGoodToAlign defaults to false when the check is not being performed.
An additional check has also been dded to ensure that there is GPS data to fuse before we declare ready to use GPS.
Switching in and out of aiding modes was being performed in more than one place and was using two variables.
The reversion out of GPS mode due to prolonged loss of GPS was not working.
This consolidates the logic and ensures that PV_AidingMode is only changed by the setAidingMode function.
Co-variances were being re-zeroed after being set. This meant that the initial declination learning was sensitive to measurement errors which could result in poor initial yaw accuracy.
IMU data was being corrected before being used by the co-variance prediction, whereas the delta angles and velocities in the derivation were supposed to be uncorrected.
This patch creates separate variable for the corrected data
Sensor bias corrections were being applied to the incoming IMU data using the wrong delta time.
This was what was driving the different tuning between plane and copter for gyro bias process noise so the same gyro bias process noise default tuning value can now be used for all platform types.
Sensor bias corrections were being applied a a second time to the output observer inertial data.
The problem with using min() and max() is that they conflict with some
C++ headers. Name the macros in uppercase instead. We may go case by
case later converting them to be typesafe.
Changes generated with:
git ls-files '*.cpp' '*.h' -z | xargs -0 sed -i 's/\([^_[:alnum:]]\)max(/\1MAX(/g'
git ls-files '*.cpp' '*.h' -z | xargs -0 sed -i 's/\([^_[:alnum:]]\)min(/\1MIN(/g'
The airspeed observation buffer was only being checked when new data arrived instead of every frame which introduced some timing jitter. The buffer is now checked every filer update step.
The duplication and inconsistent naming of booleans used to indicate availability f data has been fixed.
These changes were pair coded an tested by Siddharth Purohit and Paul Riseborough
Fix indexing errors
Move buffer code into a separate file
Split observer and IMU/output buffers and remove duplicate sample time
Optimise observation buffer search
Reduce maximum allowed fusion age to 100 msec
GPS height has been added as a measurement option along with range finder and baro
Selection of the height measurement source has been moved into a separate function
Each height source is assigned its own measurement noise
If GPS or baro alt is not able to be used, it reverts to baro
When baro is not being used, an offset is continually calculated which enables a switch to baro without a height step.
The copter method was being used for plane and the plane method was not being run due to the change in flight status not being detected.
The plane reset method did not trigger if the EKF had already dragged the velocity states along with the GPS or could align to an incorrect heading.
The method has been reworked so that it resets to the GPS course, but only if there are inconsistent angles and large innovations.
To stop a failed magnetometer causing a loss of yaw reference later in flight, if all available sensors have been tried in flight and timed out, then no further magnetoemter data will be used
Down-sample the IMU and output observer state data to 100Hz for storage in the buffer.
This reduces storage requirements for Copter by 75% or 6KB
It does not affect memory required by plane which already uses short buffers due to its 50Hz execution rate.
This means that the EKF filter operations operate at a maximum rate of 100Hz.
The output observer continues to operate at 400Hz and coning and sculling corrections are applied during the down-sampling so there is no loss of accuracy.
Large magnetometer innovations on the ground could be caused by factors that will disappear when flying, eg:
a) Bad initial gyro bias
b) External magnetic field disturbances (adjacent metal structures, placement of hatches with magnets, etc)
To avoid unnecessary switches, we inhibit switching until off-ground and when sufficient time has lapsed from power on to learn gyro bias offsets.
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.
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
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
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.
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.
priseborough
Jonathan Challinger
Andrew Tridgell
Lucas De Marchi
Siddharth Purohit and Paul Riseborough
Siddharth Bharat Purohit
Caio Marcelo de Oliveira Filho
Paul Riseborough