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.