Re: EKF process/noise modeling with non-additive noise

So we need to determine the additive covariance matrix of the noise. I
believe you should be able to do it like this:

cov(f(v(k))
= (1st order Taylor expansion)
cov(f(p)+J_f(p)*(v(k)-p))
=
cov(f(p)+J_f(p)*v(k)-J_f(p)*p)
=f(p) and J_f(p)*p are constant so...
cov(J_f(p)*v(k))
=
J_f(p)*cov(v(k))*J_f(p)

So to conclude:
1. Compute the Jacobian (only with respect to noise v) of your non linear
model called J_f
2. Compute J_f(p) where p is the last estimation for the system state
3. Choose cov(v(k)) As a diagonal matrix with sigma^2 on the diagonal.
4. Compute J_f(p)*cov(v(k))*J_f(p)^T and use it as additive noise

I hope this works
Frank


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