Many thanks for responding. Actually I am already using a Kalman Filter - I was trying to capture the essence of the problem without the details, perhaps I simplified it too far :)
In a bit more detail, let's say that I have an acceleration signal with additive Gaussian noise. I double...
I have a signal corrupted with normally distributed uncorrelated white noise. The noise has zero mean and known variance sigma1. I'd like to recover the signal as far as possible. However, the only thing I know is that the signal itself is normally distributed also, with mean zero and known...
No, not a homework assignment - I'm many years past that! :) Its a genuine problem I need to solve. I did A-level physics 30+ years ago... but I don't have enough knowledge to figure this out - unless its simpler than I am thinking - so I've nothing really to present in terms of work so far...
I'm trying to figure the velocity (and specifically the angle) of a squash ball (for example) after being hit by a racket.
Simple case: say the ball is initially stationary (hanging in the air!) and the racket hits the ball "flat". That is the velocity of the racket it normal (perpendicular)...
I have 2 vectors in 3d space, v1 and v2.
I also have a vector representing as it happens the direction of the Earth's magnetic field, called h.
i believe that v1 and v2 are related in that v2 is some rotation around h of v1.
i would like to find that angle of rotation.
i can't just find...
bit of a delay on this thread but...
I've implemented an indirect Kalman Filter for attitude estimation, where the KF estimates the error in orientation and error in gyro bias, rather than the orientation and bias itself (these are kept external to the filter). Works pretty well - no problems...