AC3.5RC1 gps/rng/optical flow analys request

I make flight with iris and SF11 + optical flow flying in loiter mode in AC3.5RC1 and standard ek2 settings.
During flight I test to go from no gps reception zone to gps zones, also, I flight over the ground and passing over roof of disused industrial building for see how ekf handle straight range finder changes and how EK2 handle GPS glitch.
Could you please check the logs and comment what you see and maybe tell us how to tune EK2 gates and noises for improve position holding and EK2 gps lidar optflow fuse?
Thanks you.

2017-03-03 (3.0 MB)
I just flown EK3 over challenging environnements.
I started from non gps zone, perfect,
to gps zone, flown over water and near wall of disused industrial building, perfect.
At the end of flight I go back to non gps zone, and EKF crashed i think, iris go to max lean angle, I switch to stabilise for regain control. (iris is robust and perfect for this tests. :))
It is like EK3 don’t want to reject gps bad readings…
Maybe this issue just need to tune gate ore noise for gps?
And if it’s the case, could you tell me new value for remake test flight?

Also If you compare AHR2 to EK3 estimation pitch there’s 30° error.
AHR2 show reality, IRIS leaned ptich by 30° before I engage stabilize, while EK3, disoriented by the gps glitch see near 0° of pitch angle.

  1. You have high frequency vibration that is significantly degrading the height performance of the second EKF instance using IMU2 and is also affecting IMU1. This needs to be fixed. Ensure you have the pixhawk on soft mounts and do not have stiff or tight cables or anything else that could be transferring vibration into the pixhawk.

  2. Test GPS aiding without optical flow and optical flow aiding without GPS first and get both working reliably before trying to combine them.

  3. Make sure you have focussed the sensor and for the best position hold use the flow sensor binary as recommended in the wiki

  4. Do your initial optical flow testing over a level surface initially and ensure that you can get a solid position hold without GPS first

  5. Tuning the EKF is best done by logging replay data and tuning offline using the EKF replay It can be done by successive trial and error tests, but this is normally a slow and frustrating process due to the stochastic nature of the errors. You will need to understand the basics of Kalman filtering to perform your own tuning.

Thank you Paul.

About replay, can I use it with make on windows?

Sorry, I don’t know - I don’t use windows.