[time-nuts] New Subscriber, DIY GPSDO project (yes, another one)

[William H. Fite]

I appreciate this discussion. I'm a statistician, not an engineer. I teach
linear quadratic estimation, of which Kalman is the archetypal example, as
a mathematical exercise without dealing more than very superficially with
practical applications. I've been following these posts with interest.
Thanks, gentlemen.


On Tuesday, March 10, 2020, Poul-Henning Kamp <phk at phk.freebsd.dk> wrote:

> --------
> In message <be8c8c2f-217b-13b8-c9ce-c4150c549852 at rubidium.se>, Magnus
> Danielson
>  writes:
>
> >It should be said that Kalman is kind of optimum for "white" noise
> >(what-ever that is), but we are far from white noise. Variants of Kalman
> >filters use noise-colour compensation of some sort, and that kind of
> >solves some of the issues. It does not fit the problem perfectly. This
> >is why time-scale algorithms is not directly Kalman filters but only
> >Kalman-esque to some degree.
>
> And that line of thought brings us to the stochastic-ish model which
> timing.com used on three 5071A and (three?) GPS's for the LORAN-C
> modernization.
>
> It's a very interesting paper and a very good idea, which works
> becuase their frequency source "bottoms out" in the MVAR plot:
> Frequency drift would mean you too many degrees of freedom.
>
> The only chance I see of doing something like that, would be a Rb
> where the lowest point on the MVAR plot is very close to 12h, or
> even better 24h, where the GPS is similarly optimal.
>
> Que the HP5065A...
>
> --
> Poul-Henning Kamp       | UNIX since Zilog Zeus 3.20
> phk at FreeBSD.ORG         | TCP/IP since RFC 956
> FreeBSD committer       | BSD since 4.3-tahoe
> Never attribute to malice what can adequately be explained by incompetence.
>
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