Mapping program for Radio Direction Finding
In the summer of 2016 I called for help in order to create a mapping program for RDF work.
A New Zealand wizard helped me out; this genious developed just the right tool for me.
Of course, I rewarded that by sharing information he needed in the field of RDF hardware.
Now that’s what hamspirit is all about!
The program is not entirely perfect yet, so don’t bother asking for a copy.
We haven’t decided yet if it will be public domain anyway. So you will just have to be patient.
Using my Arduino based Doppler RDF (PA8W RDF-40), the RDF visualizer is fed with bearing data.
As RDF-íng in a city environment produces lots and lots of false bearings, because almost all (!) measurements will be more or less multipath measurements:
Every pole, tree, branch, car, building etc. will reflect energy in lots of directions, so what my antennas receive is a mix of the direct signal combined with thousands of reflected signals.
These all add up to a more or less corrupted bearing estimate.
So in my RDF I wrote an algorithm that exports the best bearings only, to prevent the screen being cluttered by a massive amount of false bearings.
The first results on UHF (424MHz) are shown in the below picture:
You can see lines emerging from the road I drove on, and eventually most of them cross the area under the circle, which I added by hand for explaining.
It is obvious that this fully automatic RDF system is a very powerful tool for mobile RDF work.
The driver only has to take a short peek at the screen to know what part of the city he has to address.
The experiment also illustrates that we could do with fewer lines, so the next step is to narrow down the export filter to ensure that only the very best measurements are being exported.
The result (on 433MHz) can be seen here:
Again lines emerging from the trajectory my car followed.
Still some crooked bearing lines due to massive reflections, but the bulk of the lines cross at pretty much a single block of houses.
And I can say for sure that the signal originates from there, because I double-checked that with a portable receiver and a moxon.
This experiment clearly illustrates that using a mobile RDF system in a city environment is not an easy task; there are always reflections that distort your measurements, and sometimes even overrule the direct signal, suggesting the signal is coming from an entirely other direction.
This setup however automatically collects enough data to show a clear correlation between several measurements,
reveiling a pretty good estimate where the source is located.
And that with a HAM-friendly price tag, thanks to my friend Jonathan Musther from New Zealand!
The program can be downloaded here: http://www.musther.net/RDFMapper/