Instead of having a single height source fused into the EKF and the
other ones "waiting" for a failure or the primary sensor, fuse all
sources in EKF2 at the same time. To prevent the sources from fighting against each
other, the "primary" source is set as reference and the other ones are
running a bias estimator in order to make all the secondary height
sources converge to the primary one.
If the reference isn't available, another one is automatically selected
from a priority list. This secondary reference keeps its current bias
estimate but stops updating it in order to be the new reference as close
as possible to the primary one.
- replace float32[21] URT covariances with smaller dedicated position/velocity/orientation variances (the crossterms are unused, awkward, and relatively costly)
- these are easier to casually inspect and more representative of what's actually being used currently and reduces the size of vehicle_odometry_s quite a bit
- ekf2: add new helper to get roll/pitch/yaw covariances
- mavlink: receiver ODOMETRY handle more frame types for both pose (MAV_FRAME_LOCAL_NED, MAV_FRAME_LOCAL_ENU, MAV_FRAME_LOCAL_FRD, MAV_FRAME_LOCAL_FLU) and velocity (MAV_FRAME_LOCAL_NED, MAV_FRAME_LOCAL_ENU, MAV_FRAME_LOCAL_FRD, MAV_FRAME_LOCAL_FLU, MAV_FRAME_BODY_FRD)
- mavlink: delete unused ATT_POS_MOCAP stream (this is just a passthrough)
Co-authored-by: Mathieu Bresciani <brescianimathieu@gmail.com>
fix test by reducing the distance to the new origin: the maximum size of
the local position origin is a cube of 1e6m. If the origin is moved
further than this, the state is clipped to that maximum value
- refactor updateQuaternion() to compute the yaw jacobian directly (respecting the rotation sequence determination)
- fuseHeading()/fuseYaw321()/fuseYaw312() helpers are eliminated and now mag heading fusion and EV yaw fusion compute the innovation in place
- clear up logic for performing zero innovation heading fusion when quaternion variance exceeds threshold (no more _is_yaw_fusion_inhibited flag manipulation)
- when at rest continue fusing last static heading with very low variance even if other heading sources are active
- move vehicle at reset detection ekf2 -> land_detector
- ekf_unit: reduce init period
- Fake fusion is when at rest is quite strong and makes the variance reduce rapidly. Reduce the amount of time we wait before checking if the variances are still large enough.
- ekf_unit: reduce minimum vel/pos variance required after init
- Fake pos fusion has a low observation noise, making the vel/pos variances reduce quickly.
Co-authored-by:: bresch <brescianimathieu@gmail.com>
- introduces new parameter EKF2_PREDICT_US to configure the filter
update period in microseconds
- actual filter update period will be an integer multiple of IMU
Using make tests in docker will fail, because the current basic image used by px4io/px4-dev-simulation-bionic is ubuntu18.04, the default version of cmake is 3.10, and the add_compile_definitions command is only available in cmake 3.12+(ubuntu 20.04).
an airpseed of > 2m/s is required to start the fusion (set by param)
fw mode is also required
Given the larger estimated windspeed after those changes, the change of
static pressure is larger and the height estimate takes more time to
reach the final value
A constant large value in the (signed) normalized innovation test ratio is a sign
of bias in the state estimate. This metric can be used to trigger a
covariance boost or reset
Some receivers are initializing to some heading and then resetting to
the correct one after a couple of seconds. EKF2 should detect that and
reset to the new value
bresch