when using a vision position system, the user may have vision derived
GPS data coming in using GPS_INPUT msgs. We should not fuse these when
EK2_GPS_TYPE=3 as we end up fusing both vision data and GPS data,
which does not work with the current EK2 code
This change makes it possible to run EK2 and EK3 in parallel in a
Vicon, wityh EK2 using VISION_POSITION_ESTIMATE data and EK3 using
GPS_INPUT (with yaw) data.
this prevents the EKF origin on different cores from being initialised
to different values. A common value is stored in the frontend and used
by a core if it doesn't have an origin
this allows us to learn the gyro biases each lane would need if it had
to switch to another gyro due to a sensor failure. This prevents a
sudden change in gyro bias on IMU failure
this sets a limit on the difference between the earth field from the
WMM tables and the learned earth field inside the EKF. Setting it to
zero disables the feature. A positive value sets the limit in mGauss.
when we had 3 compasses the lack of the 'break' meant when we switched
compass in flight we would always switch back instantly to the one
that we had just rejected.
Fix rounding error bug preventing state from updating after initial convergence.
Decouple GPS reference height from published EKf origin height.
Add bitmask parameter to control update and publishing of GPS reference height.
this changes the stragegy for load levelling between EKF cores so it
works between EK2 and EK3, and with future estimators as well.
It allows us to run EK3 and EK2 at the same time with good scheduling
performance
Correction requires the body rates averaged across the flow sensor sampling interval. This data has been added to the sensor buffer.
The body rate data from the flow sensor driver does not contain the Z component, so an equivalent value sampled from the navigation IMU has been used instead.
The variable omegaAcrossFlowTime has been moved out of the class and into the only function that uses it.
A specialised takeoff check is now always performed when we receive new flow data as the default behaviour is to try and use flow data whenever it is received, rather than limit its use to a use to a flow-only mode of operation that had to be selected via user parameter.
The EK2_RNG_USE_HGT parameter sets the height (expressed as a percentage of the maximum range of the range finder as set by the RNGFND_MAX_CM parameter) below which the range finder will be used as the primary height source when the vehicle is moving slowly.
When using a height reference other than GPS, the height datum can drift due to air pressure changes if using baro, or due to terrain height changes if using range finder as the primary height source. To ensure that a consistent height datum is available when switching between altitude sources, the WGS-84 height estimate of the EKF's local positi norigin is updated using a
single state Bayes estimator,
If rngfinder or gps height data is lost whilst being used, there will be a fall-back to baro data.
When switching over to a back up magnetometer, ensure that the earth field estimate are reset. other wise mag earth field estimates due to the previous failed mag could cause data from the new mag to be rejected.
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.
Peter Barker
Michael du Breuil
Andrew Tridgell
Pierre Kancir
Tom Pittenger
chobits
Dr.-Ing. Amilcar do Carmo Lucas
Paul Riseborough
Randy Mackay
Mathieu OTHACEHE
Jonathan Challinger
Lucas De Marchi
Siddharth Purohit and Paul Riseborough
Siddharth Bharat Purohit
Caio Marcelo de Oliveira Filho
Paul Riseborough