[Bayes++] The difference between "observe" and "observe_new" in SLAM class

[Robert Z. <eer...@ya...>]

=0AThanks for your help, Michael. =0A=0AActually, my research focuses on SL=
AM and I hope to use the SLAM class that you have done. I am confused by tw=
o member functions in this class, the "observe" and "observe_new". Could yo=
u explain them more in detail?=0A=0AI look forward to hearing your reply.=
=0A=0ARegards,=0AZhang Xinzheng=0A=0A--------------------------------------=
---------------------------------------------------------------------------=
---------------------------------------------------------------------------=
---=0AOn Tuesday 30 October 2007, Robert Zhang wrote:=0A> > Dear all,=0A> >=
=0A> > I have read the post name "Covariance matrix Q" in this mail list. I=
 have a=0A> > question on the covariance matrix R which is used in the line=
arize observe=0A> > model when the EKF is employed. Is it generated similar=
 to Q? However, I do=0A> > not find any Jacobian matrix same as G in the =
=0A> > "Linrz_uncorrelated_observe_model. Thanks for any help.=0A> =0A> The=
 observation covariance matrix R is used directly in Bayes++. For =0A> nota=
tional consistency it is call 'Z' in the Bayes++ observe models.=0A> =0A> T=
herefore in 'Linrz_correlated_observe_model has a symetric matrix (SymMatri=
x)=0A> called 'Z'.=0A> =0A> It is very common that the addative noise in ob=
servation models are =0A> uncorrelated. In this case 'Z' is a diagonal matr=
ix. You can then use =0A> the 'Linrz_uncorrelated_observe_model' where the =
vector 'Zv' represents =0A> observation variances.=0A> =0A> For example if =
you have a range+angle measurement (such as a Radar) you can =0A> normally =
model the measurement as having addative noise in range and addative =0A> n=
oise in angle. These are usually uncorrelated. You can then measure/guess =
=0A> their variances and place them in Zv[0] and Zb[1].=0A> =0A> Regards,=
=0A> Michael=0A> -- =0A> ___________________________________=0A> Michael St=
evens Systems Engineering=0A> =0A> 34128 Kassel, Germany=0A> Phone/Fax: +49=
 561 5218038=0A> =0A> Navigation Systems, Estimation and=0A> Bayesian Filte=
ring=0A> http://bayesclasses.sf.net=0A> ___________________________________=
=0A =0A--------------------------------------------------------------------=
---------------------------------------------------------------------------=
------------------------------------------------=0A=0A=0A=0A_______________=
___________________________________=0ADo You Yahoo!?=0ATired of spam?  Yaho=
o! Mail has the best spam protection around =0Ahttp://mail.yahoo.com