This commit introduces a quality measure in the range data. It is
used to properly decide whether to initialize the HAGL estimate on
sensor data or MIN_HGT parameter, as well as in the decision of
whether a 'fake' measurement should be published on the ground to
allow for optical flow take-offs.
This adds support for the paparazzi autopilot to use this library as EKF.
The header order change has to be done in order to have std.h included to get certain defines at the start of the estimator_interface.h.
Fusion with large initial magnetometer biases errors can result in the the NE earth field states reducing in magnitude and effectively flipping sign.
EKF: Move declination state limiting into a separate function
EKF: Limit NE mag states after each 3-axis mag fusion
EKF: Fix bug in mag field strength look-up scale factor
Heading data is assumed to be from a dual antenna array at a specified yaw angle offset in body frame, but with the heading data already corrected for antenna offset. The offset is required to apply the correct compensation for combined rotations and to determine when the yaw observation has become badly conditioned.
This brings all the range finder data checks (excluding innovation consistency checks) into one place and eliminates the need to perform range checking external to the library.
The hard coded optical flow tilt limit is changed to use the same value as the range finder.
Variable names are changed to make a clear distinction between the max/min values calculated by the stuck range check and the max/min valid values for the sensor.
* EKF angle constants in degrees for readability
* EKF make FILTER_UPDATE_PERIOD_MS static constexpr and add FILTER_UPDATE_PERIOD_S
* EKF controlOpticalFlowFusion() use constants and update comments
* EKF controlMagFusion() use angle in degrees
* EKF move earth spin rate to geo and update usage
* EKF: Fix numerical constant error and clean up comments
Comments do not need to contain numerical values when the code makes these clear.
* EKF collect_imu take const imu sample and populate buffer
* EKF calculateOutputStates cleanup
* EKF add calculate_quaternion output predictor method
* EKF: update documentation
* EKF: remove unnecessary getter function
* EKF calculateOutputStates only apply dt correction to bias
* EKF pytest assert attitude validity, not update() return
* EKF: correct documentation
* EKF: Do not make attitude validity dependent on yaw alignment status
Yaw alignment could fail in flight due to temporary loss of data and yet the quaternions would still usable for stabilisation even though the absolute earth yaw angle wrt true north was uncertain.
Remove duplicate checking for dead reckoning and consolidate into a single function.
Use separate timers to check for start of dead reckoning and check when dead reckoning has been performed for too long for the nav solution to be valid.
Allow the timeout for validity reporting to be adjusted externally.
Separate external reporting of dead reckoning from internal checks.
This enables the EKF to use an additional NE velocity measurement. This can be used to improve position hold stability when landing using a beacon system for positioning by fusing the beacon velocity estimates.
Apply a dead-zone to the vertical position innovation if using baro for height and if in the ground effect region during and just after takeoff.
Method needs to be activated externally.
Turns off automatically after 10 seconds or if specified height gained.
Reduces susceptibility to incorrect estimation of acceleration bias during sustained yaw rate.
Requires an increase in RAM allocation of 837 Bytes to allow for the longer IMU and output predictor buffers that can be created.
Julian Kent
Nico van Duijn
kamilritz
bresch
Robert de Vries
Carl Olsson
Nuno Marques
Daniel Agar
Freek van Tienen
Paul Riseborough
Paul Riseborough
Mohammed Kabir
ChristophTobler