Allow different process noise to be set for body (sensor bias) and earth field states.
This allows a stable magnetometer bias estimate to be available at end of flight whilst still allowing for external magnetic anomalies during landing.
Adjust default values to give stable mag bias learning and fast learning of external anomalies.
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.
M_NSE is a measurement noise
P_NSE is a observation noise
I_GATE is an innovation gate
This also ensures the new parameter values required to use the EKF2 will be enforced.
Change to user adjustable fusion of constant position (as per legacy EKF) instead of constant velocity.
Enable user to specify use of 3-axis magnetometer fusion when operating without aiding.
Don't allow gyro scale factor learning without external aiding data as it can be unreliable
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.
Eliminate the use of horizontal position states during non-aiding operation to make it easier to tune.
Explicitly set the horizontal position associated Kalman gains to zero and the coresponding covariance entries to zero after avery fusion operation.
Make the horizontal velocity observation noise used during non-aiding operation adjustable.
Use a fixed value of velocity noise during initial alignment so that the flight peformance can be tuned without affecting the initial alignment.
The ad-hoc scaling of error growth has been replaced with a consistent method that uses the main nav filters published vertical velocity uncertainty and the terrain gradient assumption.
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.
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.
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
Paul Riseborough
Jonathan Challinger
Tom Pittenger
Ricardo de Almeida Gonzaga
Andrew Tridgell
Don Gagne
Siddharth Bharat Purohit
Paul Riseborough