[Salik Syed]

Yes, you're right. A kalmann filter is only really effective when dealing White Gaussian noise. The noise we are dealing with in the gyro is still of this quality, It is integrated over time yes, but the noise in the measurement from the gyro itself is not non-gaussian. Based on this principle as the time variable increases the probability distribution of the estimate produced by the gyro "widens" ... it's measurement simply becomes more and more unreliable. Now if the Gyro happened to have different levels of noise at different levels of acceleration we would have a real problem... but it since the noise distribution from the sensor itself is white and gaussian Kalmann filtering will work. (not as effectively of course... but it can be used)

BTW
For those of you who don't know what that is here's a simple explanation:
White noise basically means that the noise in the current state has no bearing on noise in the next. Basically it means that the noise is "random".
Gaussian relates to the amplitude of the noise. A gaussian distribution is basically a "bell curve". If noise is gaussian it means the probability distribution of the amplititude of the noise will be a bell shaped gaussian curve.

I don't think there's an effective way to account for drift using Kalmann filters alone, Although since you know when you are standing still (with almost 100% certainity) you can basically give the Gyro a very narrow probability distribution at the start along with the somewhat wide distribution of wheel encoders, then as you build a better model through the kalmann filter re-adjust the gyro bias to lineup with your best estimate (using measurement from both sources: wheel encoders AND gyro itself). It's rough at best but certainly better than just integrating the gyro to read an angle.

Also the Kalmann filter does take into account integrated estimation error by basically "widening" the probability distribution over time, if a gyro is off by a little bit it's error will be summed over time... This is how it can be used when dealing with velocities