Quiet Baseline for Longwave - Part 1

Ionospheric propagation is probably my number one radio interest, particularly the idea of prediction so that I can choose the best frequency or time or, ideally, the best date for a particular path.

We have these general rules about moving up and down the bands according to how high the sun is above the horizon and where we are in the sunspot cycle and propagation software that incorporates these factors has been around for years but I would like to do better than that, especially since I am interested in low power communications.

One problem with programs like VOACAP is that almost all of the work has gone into the HF part of the spectrum from 3 MHz to 30 MHz but these days I am mostly interested in the lower frequencies, partly because we are at the bottom of the sunspot cycle and partly because of the new 630 m and 2200 m allocations.

After almost a year and a half of renovating the home I moved into in 2017, I finally have a couple of descent wire aerials installed. My first project is to evaluate my local noise level under quiet solar and geomagnetic conditions and to get some quantified baseline of what to expect as "normal" propagation so that I can recognize unusual conditions when they occur.

Aircraft NDBs are wonderful for studying frequencies below 3 MHz because, unlike medium wave broadcasters, they transmit 24/7 without changing power or their antenna patterns and they constantly identify in slow Morse.

I spent much of this month collecting longwave data by recording NDBs with a Perseus SDR. My original idea was to record from 135 kHz to 535 kHz for two minutes every hour for at least three consecutive days with quiet solar and geomagnetic indices and then chart the carrier strength for each signal I found. Since this is winter, QRN from northern hemisphere storms should be low enough to give me a good chance at capturing some of the weaker signals.

Unfortunately, the human element of this did not go well. The best I could do was get through three hours of data in one hour. Manually estimating and recording signal strengths just took too long, especially for weak signals where I sometimes had to spend 10 minutes replaying a file to pull a single ID out of the noise. For 72 files it would have taken me about 50 hours just to do the data entry.

Then I remembered that the Perseus has the ability to place markers on up to eight frequencies and record the corresponding signal strengths to a text file at regular intervals along with a timestamp.

Eight was not ideal because a typical evening file had 15 identifiable signals. Still, about 10 of those were nearby “daytime regulars” of little interest for studying ionospheric propagation so eight markers should be enough for the more variable distant signals.

One weird thing I discovered is that, even when automatically logging markers from a previously recorded file, the timestamps were for the current UTC of when I was playing back the file, rather than when the file was recorded. That was a nuisance but I was able to work around it. The marker signal strength file is always named markers.log and old versions get overwritten by new ones so I included the timestamp of the original recording when renaming the file. That made it available for use when analyzing the data.

The above graph shows my result from a single 24-hour period (2018-12-06 UT). The vertical scale is in dBm but I only care about the shapes of the curves. The following graph is the result of averaging the respective ToH values over 4 consecutive UT days (2018-12-06 to 2018-12-09). Correction to both charts: The ID for 284 should be QD.

Q: What can I conclude from this?
A: Not much, other than "Distant signals are stronger at night." but this is nothing new.

That's why this post is Part 1.

Before this line of enquiry can be of any use to me, more work will be required:

1. The 284-MB signal from The Pas, Manitoba indicates a problem. It's one of the weakest regular nightly signals here but both graphs show it as being surprisingly strong during the day and not changing much at night. That's because that part of the spectrum was consistently noisy and the marker's bandwidth was between 200 and 300 Hz with the settings I had to use to span all eight frequencies. A future attempt at this should record only four stations and use the other four markers to record only the adjacent noise so that it can be subtracted.
2. Recording only the markers, as opposed to recording raw spectrum, generates very little data so next time I will sample the carriers much more often. I should not have chosen smoothed curves when producing these graphs because they are misleading considering the hourly sampling windows.
3. The eight stations were chosen for geographic diversity. I was hoping to see trends like a peak moving from east to west but that was too ambitious for only eight signal sources. Next time I should do something like comparing a group of four Manitoba stations to a group of four Alberta stations averaged over several consecutive nights of similar quiet solar and geomagnetic conditions.

The work to this point has not been a waste of time because it has served as a "shake out" to see what is realistic. I hope to come away from subsequent experiments with a general idea of how a typical night of longwave behaves. A bonus would be to come up with a credible strategy for targeting the states and provinces that are still missing from my log, especially since I decided to reset it to zero at this new QTH.

Once I get that sorted out I would like to compare propagation on nights of quiet solar and geomagnetic conditions to nights of more active or disturbed conditions as we claw our way out from the bottom of the sunspot cycle. Even if nothing meaningful comes of it I should at least have good data from which to draw that conclusion.