Down the rabbit hole

In my quest to learn everything there is about creating amateur UAVs, I often find myself on the discussion boards of RCGroups, where I’m fascinated by the posts of one "Jack Crossfire", who writes like Hunter S. Thompson if he were an out-of-work programmer on a quest to build the ultimate heli UAV. I’m clearly […]

Thumbquat_noise_0_01
In my quest to learn everything there is about creating amateur UAVs, I often find myself on the discussion boards of RCGroups, where I'm fascinated by the posts of one "Jack Crossfire", who writes like Hunter S. Thompson if he were an out-of-work programmer on a quest to build the ultimate heli UAV. I'm clearly in the presence of some sort of technical genius from whom I could learn loads, if only I had any idea what any of this meant:

"So in our AHRS simulator, with full sensor data, the Kalman filter was much more stable than it was with just gyros. The results were unexpected. Instead of optimum damping constants, it uses the heading noise factor and ignores the other constants.

We have graphs of the quaternion output of the Kalman filter using different heading noise and a graph using the Hudson/Kahn factors. The data was of the sensors sitting on the floor in the dumpy apartment."

Is this what it's going to take for us to make a working autopilot? Has it really come to the quaternion output of Hudson/Kahn factors? Yikes.