Re: [Bayes++] Covariance matrix R

[Michael S. <ma...@mi...>]

On Tuesday 30 October 2007, Robert Zhang wrote:
> Dear all,
>
> I have read the post name "Covariance matrix Q" in this mail list. I have a
> question on the covariance matrix R which is used in the linearize observe
> model when the EKF is employed. Is it generated similar to Q? However, I do
> not find any Jacobian matrix same as  G  in the 
> "Linrz_uncorrelated_observe_model. Thanks for any help.

The observation covariance matrix R is used directly in Bayes++. For 
notational consistency it is call 'Z' in the Bayes++ observe models.

Therefore in 'Linrz_correlated_observe_model has a symetric matrix (SymMatrix)
called 'Z'.

It is very common that the addative noise in observation models are 
uncorrelated. In this case 'Z' is a diagonal matrix. You can then use 
the 'Linrz_uncorrelated_observe_model' where the vector 'Zv' represents 
observation variances.

For example if you have a range+angle measurement (such as a Radar) you can 
normally model the measurement as having addative noise in range and addative 
noise in angle. These are usually uncorrelated. You can then measure/guess 
their variances and place them in Zv[0] and Zb[1].

Regards,
	Michael
-- 
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Michael Stevens Systems Engineering

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Navigation Systems, Estimation  and
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