Re: [Bayes++] Square-root UKF

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

On Thursday 11 January 2007 18:01, you wrote:
> On 1/11/07, Michael Stevens <ma...@mi...> wrote:
> > Hello Matt,
> >
> > On Wednesday 10 January 2007 00:14, Matt Hazard wrote:
> > > Is there any support for Square-root (cholesky decomposition, etc)
> > > formulations of the Unscented Kalman filter in Bayes++?
> >
> > Sorry there are no Square-root Unscented implementations in Bayes++. The
> > only
> > unscented filter implemented is that described in the original Unscented
> > paper. Simon (Julier) has
> >
> > > I'm working on a
> > > GPS/INS system purposed for real-time control of a helicopter UAV; any
> > > computational cost reduction on the estimation end could directly lead
> >
> > to a
> >
> > > performance gain in the controller.
> >
> > OK I have a lot of experience in the GPS/INS fusion field so maybe I can
> > help
> > here. I would be interested in what sensors you are using.
>
> Our sensor board prototype uses Analog Devices' gyros (ADXRS300) and
> accelerometers (ADXL330, I think). The magnetometer is a PNI MicroMag3. We
> also have a complete (working) Crista IMU, which uses basically the same
> gyros/accelerometers, but lacks the magnetometers. At any rate we should
> see comparable results between the two sensor packages.

OK. Low cost MEMS type sensors. With this kind of low accuracy sensor you will 
need good differential GPS position to maintain the platform attitude.

The Crista unit look very sensible. It avoid ny attitude processing, which 
usually gets in the way. The temperature compensation and 1pps syncronisation 
are are worth having.


> > > I'm using an Addative_predict_model and an
> > > Uncorrelated_addative_observe_model. Are there underlying assumptions
> >
> > for
> >
> > > these models that make them less suitable than the base model
> > > (Unscented_scheme::observe, for instance?)
> >
> > I am a bit confused by you "base model". 'Unscented_scheme::observe' is a
> > member function of Unscented_scheme.
> > Specifying the model as 'Uncorrelated_addative_observe_model' is fine for
> > the
> > Unscented_scheme however.
>
> My mistake. I  copied the wrong thing. What happens if I use the
> uncorrelated noise model and the noise turns out to be correlated?

Not a problem for the Unscented_scheme. For most square root filters it is 
however a problem! The factorisations use to put the system into squareroot 
form require that the noise can be decorrelated and there is only a general 
solution for this for linear observation models. Luckily most observation 
generally only have weak cross correlations!

Michael
-- 
___________________________________
Michael Stevens Systems Engineering

34128 Kassel, Germany
Phone/Fax: +49 561 5218038

Navigation Systems, Estimation  and
                 Bayesian Filtering
    http://bayesclasses.sf.net
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