Simple Kalman Filtre with 2-D state vector
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Thank you very well Geoff. I do it with your helps. Thanks
2 Comments
Geoff Hayes
on 12 Jan 2017
bahadir - what is your question? Because it almost looks like you have posted homework and are asking (or expecting?) someone to do it for you. Please attempt the problem and then post questions concerning what you have tried (include any errors that you have observed).
You seem to be tasked with implementing a Linear Kalman Filter. You have the algorithm and all of the (noise, covariance, etc.) matrices so what is missing?
Accepted Answer
Geoff Hayes
on 12 Jan 2017
bahadir - unless you have an algorithm to estimate what R(t) and Q(t) should be at time t, then I would just use the R and Q that have been defined above for all t. This should be sufficient.
Since there is no action, then I suspect B can be zero.
As for Sigma(t) (your E(t)), this is your covariance matrix. Given how it is updated at step three, I suspect that you can initialize it to R...so Sigma(0) = R.
As for your last point, I'm not sure what you mean by &t. Do you mean delta t? If so, it can probably be zero or you can randomly generate it at each iteration using the zero mean and Q for this Gaussian distribution.
5 Comments
Geoff Hayes
on 14 Jan 2017
Yes, I could write a simple Kalman filter in Matlab using your parameters for only one iteration. But then that would be doing your homework for you... ;)
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