I'm interested, how is the dual input in a sensor fusioning setup in a Kalman filter modeled?
Say for instance that you have an accelerometer and a gyro and want to present the "horizon level", like in an airplane, a good demo of something like this here.
How do you actually harvest the two sensors positive properties and minimize the negative?
Is this modeled in the Observation Model matrix (usually symbolized by capital H)?
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