Lay off the guy. The fact is that the Kalman filter applies to a very small (arguably non-existent in the real world) set of estimation problems, and the solutions that even the PhDs come up with are typically ad hoc and suboptimal.
That being said, there's really not much to his solution - he's relying on gravity (from accelerometer) and magnetometer data to provide most of the orientation information. The IMU really isn't doing much, and I can't see how this works well during maneuvers.
EDIT: Note that's the _actual_ Kalman filter. Most of the time when people say KF, they really mean Extended Kalman Filter, which is an approximation to the real thing. Optimality goes out the window when you approximate.
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Lay off the guy. The fact is that the Kalman filter applies to a very small (arguably non-existent in the real world) set of estimation problems, and the solutions that even the PhDs come up with are typically ad hoc and suboptimal.
That being said, there's really not much to his solution - he's relying on gravity (from accelerometer) and magnetometer data to provide most of the orientation information. The IMU really isn't doing much, and I can't see how this works well during maneuvers.
EDIT: Note that's the _actual_ Kalman filter. Most of the time when people say KF, they really mean Extended Kalman Filter, which is an approximation to the real thing. Optimality goes out the window when you approximate.