pms67 / ekf-quaternion-attitude-estimation Goto Github PK

Hi,

First of all, very great work ! It's not an issue, it's just a question about your code.
I have a board build witn an gyro and accel, I don't have mag, is it possible to use your code without mag? What the results if I don't provide any data or zero data for mag?

Can I set mag values at 0 also Va airpseed?

Thanks

I'm building a weighing system. Here I filter analog data with kalman filter and moving average. I have a problem like this.

I put 2 kg on the scale and shake the weighing mechanism and create vibration. In this case, the 2 kg value moves +- 20 grams. If I increase my filtering coefficients, this play disappears, but this time the system reacts very slowly to changes of 1 gram. How can I solve this problem can you help me.

Link http://philsal.co.uk/quaternion-based-extended-kalman-filter-for-fixed-wing-uav-attitude-estimation is dead

If I understand it right, If I had only the the accelerometer without the magnetometer then the C matrix ( observation) would change by removing the last 3 rows. Moreover , what if I didn't have the Va ? how the accelerometer model look like then ? should I just assume it to be zero ?
I mean I only have the accelerometer in my update step.
Thanks

and by the way .. great work !

Hi
great work
I have already done the state estimation with linear Kalman filter... Now I want to do it with your Code (EKF) and publish the comparison...
but I need more description of how you matlab function works
I added that to my simulink model as matlab function that updates each iterates
I have a few questions:
What is Va? How should I know the velocity?? I dont have the velocity value :|
I ran the simulation with :
Va , MagDec = 0
NDivT =1
but I got NaN value as output

Can you please help me with an example for implementing your code in a working project?
I will publish the comparison result in youtube and put the link to your github as source
Thanks