Process Noise “Q” covarience matrix in a kalman filter

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Farhan on 16 Sep 2014
Answered: John Petersen on 2 Oct 2014
I am trying to implement a Kalman filter on a Phasor Measurement Unit (PMU) values. I meaured the signal from PMU and give those meaurement as input to Kalman filter to get best estimate. I do not have a Process model. I assume A, B, C and D matrices.
My question is while calculating Q covarience matrix (process noise) in MATLAB, should i give the whole measurement as input to "cov" function in MATLAB or instead of whole measurement i should give the error(actual- measurement) to "cov" function to calculate Q?
Please guide me? Thanks in advance.

Answers (1)

John Petersen
John Petersen on 2 Oct 2014
The measurement error is not used to update any covariance matrices in a Kalman filter.

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