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.
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.
The filter status logic calculations were being repeated every time the get function was called.
The logic is now updated once per filter update step and a separate get function added
If we start GPS aiding before the gyro bias variances have reduced, glitches on the GPS can cause attitude disturbances that degrade flight accuracy during early flight.
Remember the mag bias and earth field states learned during flight when the vehicle lands.
This improves performance for vehicles that do multiple flight on one power cycle
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
Automatically use the highest gain consistent with a 5% overshoot to minimise RMS tracking errors.
Provide an alternative correction method for the position and velocity states that allows the user to specify the time-constant. This can be used to fine tune the output observer for for platform specific sensor errors and control loop sensitivity estimation noise.
The toilet bowling check during early flight has been removed. This check caused problems where bad compass calibration was the cause of the toilet bowling and resetting to the compass was a bad option. The handling of simultaneous failed mag and velocity innovations is already handled outside the EKF by the failsafe.
A check for yaw errors due to a ground based magnetic anomaly has been introduced.
The logic for in-flight yaw and magnetic field resets has been cleaned up and variable names improved.
Splits in-flight yaw alignment completed status into separate yaw and magnetic field flags.
Reduce the number of places where decisions to perform a yaw and field reset are made.
Don't perform a reset unless there is is data in the buffer
Don't use 3-axis fusion if the field states still need to be reset.
When starting 3-axis fusion request a reset if not previously performed.
Ensure magnetometer and GPs heading resets are alwasy perfomred with data at teh correct time horizon.
When changing the vehicle yaw angle, the correlation between the attitude errors and errors in other states is invalid so the corresponding co-variance terms need to be zeroed.
This needs to be done in more than one place.
Implements the following techniques to enable planes to operate without magnetometers.
1) When on ground with mag use inhibited, a synthetic heading equal to current heading is fused to prevent uncontrolled covariance growth.
2) When transitioning to in-flight, the delta between inertial and GPS velocity vector is used to align the yaw.
3) The yaw gyro bias state variance is reset following an in-flight heading reset to enable the yaw gyro bias to be learned faster.
Use an Euler yaw heading that switches between a 321 and 312 rotation
sequence to avoid areas of singularity. Using Euler yaw decouples the
observation from the roll and pitch states and prevents magnetic
disturbances from affecting roll and pitch via the magnetometer fusion
process.
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.
