I've been into FPV for a few months now, and one of the things I've wanted to do was visualise practice race courses over the top of the FPV video feed. That way I can practice courses at a higher altitude, with more variations, in a space (think: park) that in itself may have no natural obstacles.
I've spent some time doing research, and think it can be done using IMU/Baro/GPS + EKF, hopefully yielding an "accurate enough" position. It doesn't have to be perfect, I'd say as long as the position isn't jumping around by more than 20cm it would be usable. I've played with a couple of 9/10DOF IMU sensors and have a GPS sitting on my table ready to use.... except I'm getting stuck at the "how do I fuse that with the other sensor values?" part.
I've read Simon Levys excellent EKF tutorial (http://home.wlu.edu/~levys/kalman_tutorial/) and I understand most of it. It doesn't go into enough detail for me on how I'd get GPS into the mix, nor do I understand how I form the Jacobian matrices. It's right at that part that my eyes begin to glaze over. I feel like I need help with that particular piece as it's clearly not my area!
Can someone with more experience perhaps guide me in either what I should read, or code that I could adapt? My goal at this stage is to develop & understand enough that I am processing the raw sensor values, mixing that with the GPS via EKF and ending up with coords that I can use.
I've found various examples that run filters over accel / gyro data, but nothing that is mixing both the integrations of those (to get IMU based position), with GPS data that is supplied at a lower Hz.
Open to any help or suggestions!