I posted this earlier but did some tweaking on it to compare the Extended Kalman to my Fixed Gain Observer filters. I haven’t finished the FGO position filter but am really starting to lean more on EKF because the performance really is significantly better.
The idea for this filter is to fill in the gaps of the GPS position between the 1-4 Hz range for something like a quadrotor or just overall improved lag free navigation. You can clearly see how the fusion of more sensors can really increase your UAV's perception of reality!
**Edit, I improperly emulated GPS in the first pic so I added the correct pic. This shows how GPS comes in at 2Hz with noise and using a little logic and deadreckoning you can not only fill in the gaps but be more accurate than GPS is actually reporting. The GPS acts kinda like the accelerometers in the DCM algorithm, they keep the solution constrained.