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Kalman filter versus exponential filter

I was wondering what are the advantages and disadvantages of the Kalman filter and the Exponential filter ? I have a problem with multiple sensors, and I'm trying to decide which method to choose.

I think that the Kalman filter is more complicated, but has a more detailed model of the system, so it is more accurate (?) When merging with several sensors.

While an exponential filter is a simple equation, it is limited by alpha (higher alpha = less filter “memory” and therefore less smoothing, but more significant for measurements, while lower alpha has a higher degree of smoothing but sudden changes are not reflected properly.

An exponential filter is more useful for noise reduction when there is jitter, etc., while a Kalman filter is useful for actually merging several sensors. Is it correct?

Also, how useful is the Genetic Algorithm for sensor fusion? I am trying to combine a magnetic compass and a gyroscope to assess the true orientation.

Thank!

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"What are the advantages and disadvantages of the Kalman filter and the exponential filter? I think the Kalman filter is more complicated, but has a more detailed model of the system, so it is more accurate (?) when merging with several sensors.

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