I've tried to make adaptive Kalman filters work, and it's not easy. For something like a rocket, the covariance of all the sensors is very low while it's sittin

I've tried to make adaptive Kalman filters work, and it's not easy. For something like a rocket, the covariance of all the sensors is very low while it's sitting on the launch pad. As soon as you light the engines, the covariances jump up. So an adaptive filter will try to adjust its weights during the first few seconds of flight, which is a terrible time to change everything. Usually it's better to lock down all the filter coefficients. Also, an adaptive Kalman filter measures noise on each input to estimate error, usually by looking at the autocovariance. This turns out to be maximally bad when a sensor fails and emits a constant value, because the autocovariance becomes zero and the adaptive filter will decide it's the most accurate of all the inputs and weight it heavily. Before a Kalman filter, you need redundant sensors and logic to discard ones that disagree with the majority. Angular rate sensors and accelerometers are cheap and light, so I'm sure they have at least 3 sets. Maybe 5.