#StackBounty: #kalman-filter #state-space-models How to estimate parameters of an Extended Kalman Filter

Bounty: 50

I am slightly familiar with how to estimate the parameters in a linear Kalman Filter, by using maximum likelihood. Do we do the same for the extended Kalman Filter? In particular, I am confused as to how to set up the log likelihood equation. the general expression that I have seen so far involves some integrals, and it is not clear to me exactly whether it is just the product of normal distribution or not

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