I recently became interested in radio propagation science. I highly recommend the recent ARRL publication, Propagation and Radio Science, by Eric Nichols, KL7AJ if you are also interested in these things. One of the main themes of the book is that the effects of the Earth’s magnetic field plays an underappreciated role in radio propation. In particular, the magnetic field causes radio waves to split into two parts, labeled the ordinary and extraordinary rays, O ray and X ray, respectively. Both of these rays are now circularly polarized in opposite directions. Because the O and X rays have different refractive indices, they travel different paths through the ionosphere and not always in ways you might expect. You can see the split on an ionogram. The pink trace represents the O ray, and the green trace is the X ray. Also shown is the total electron content, or TEC (the black curve in the ionogram). You can browse ionosonde data here, navigate to a station, date, and time of interest and see the ionograms for yourself. It’s interesting to see how the data change with local time of day, or with significant solar events.
APRS for Science!
I mentioned in a previous post that I attended the fall meeting of the American Geophysical Union in December. I happened across a poster presentation by Alex Cushley (VA3CUS) and Jean-Marc Noël (VA3CIM) about using amateur radio signals to conduct propagation science. They proposed a method for determining TEC using APRS signals as well as automatic dependent surveillance broadcast (ADS-B) signals. ADS-B is used in the aviation business, and is similar to APRS, but for aircraft, and operates on 1090 MHz. Because the signals are affected by the magnetic field as they pass through the ionosphere, as noted above, the authors of this study suggested measuring the degree to which APRS and ADS-B signals are affected to calculate the properties of the ionosphere along that signal’s path. By performing this calculation along lots of signal paths, they can then construct a 2 or 3 dimensional model of the ionosphere during the time period and over the area in which the signals were collected. I think this is pretty clever.