Jim Lux wrote:
>I'm looking for an algorithm for my "generate all profiles for HFTA" app..
>I've taken a couple trivial shots at this, but I'm pretty sure someone
>out there knows of a "better way".
>
>here's what I want..
>
>I have an array of heights vs distance at fairly close post spacings (on
>the order of 10 meters) maybe 1000 points or so, representing the
>profile along a particular radial. What I want to do is "compress" that
>into about 100 or so segments that are connected (e.g. HFTA input).
>That is, I want to convert that to a series of x,y coordinates connected
>by straight lines that "adequately" represents the terrain.
>
>I started with a simple "if the adjacent point is within X meters in
>altitude, then collapse the two into one", but that produces profiles
>that somehow don't look right (and I can't say much about their HFTA
>fidelity). If the underlying terrain were a ziggurat or mesas with
>valleys, it would probably work, but it turns a gentle slope into a
>staircase.
>
>This is a classic problem in cartographic generalization, and, as it
>happens, this kind of profile is well represented by a fractal, but not
>that this helps me much. I was hoping that someone out there knew of a
>clever way to do it.
>
>Preferably in Python, since that's what I've written everything else in,
>but I can convert anything.. so if you have one written in COBOL, that's
>fine.
>_______________________________________________
If may be easier than you think, because HFTA already makes a linear
extrapolation between data points, regardless of horizontal separation.
Faced with 360 sets of computergenerated radial data at 100m intervals
going out to 200km, my manual algorithm was:
1. Cut off the data somewhat beyond the visual horizon. You can do this
the oldfashioned way by looking at a map, by writing your own routine
or by plotting an approximate horizon profile using www.heywhatsthat.com
2. Wherever there are >=3 points at the same height, remove all but the
first and last. Large areas of water are obvious targets [insert other
flatlander jokes here].
3. If the number of points is still too large for HFTA, consider
removing redundant data anywhere that the slope can be approximated by a
straight line between the first and last points. The further away from
the antenna, the less any errors will matter, so work inward from the
greatest distance.
4. Repeat 2 and 3 until the data set is small enough for HFTA to handle.
5. And then  most important  go outside and LOOK AT WHAT'S REALLY
THERE in the immediate foreground of the antenna.
Don't hesitate to modify the satellite data wherever you know better.
You are much closer to the reality on the ground! For example, dense
areas of trees would have given a good radar reflection from the
treetops, but at HF the true ground level will be a better
approximation.

73 from Ian GM3SEK
http://www.ifwtech.co.uk/g3sek
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