Closed desa001 closed 4 years ago
Hi,
Thanks you for your comments.
If you us an high precision imu, I suggest to first seen the RINS-W paper. With such sensor, the main source of errors is bias. I think the method suits well for correcting this bias when the vehicle is stopped.
Well I do suppose that you know the noise and the output frequency of them. If they are faut it is much better for the estimation to be postpone.
If they are high
Hi,
Thanks you for your reply.
In these two articles, the effects of earth rotation and Coriolis acceleration are ignored. However, in the high precision navigation and long distance navigation (>50km), those effect should not be ignored. In that case, the velocity of the carrier in the inertial frame is equal to $w_{ie}^i \times r^i $ when the carrier stops. Since $r^i $ is unknown, I want to ask how to use ZUPT in this case. Thanks very much.
Sure
Cf. Les travaux de Faure sur le référentiel inertiel
Personnellement, j'avais lu son bouquin "Navigation inertielle et filtrage optimal" et c'est un peu mathématique mais bon on s'habitue à tout
Désolé par Pierre Faurre
Je viens de le commander et c'est vraiment un bon livre pour mieux comprendre comment cela s'organise et fonctionne en mode inertiel.
Hi,
First thanks for your great work and open source.
I have downloaded your code and run it on my laptop, the result is really cool. But I notice that both the KITTI dataset and your another article "RINS-W: Robust Inertial Navigation System on Wheels" 's dataset the IMU gyro and accelermeter precision is really low, it break its limition and reach a good result using iekf and training methond.
Now I am working on high precision IMU navigation such as fog imu(bias stablity < 0.05 deg/h) so I just want to ask : are you think about the proposed method will have good affect on high precision IMU . I want to try, but not for sure.