Category Archives: SDR

WSPR & MH370: Richard Godfrey lügt wie gedruckt

So lügt Richard Godfrey: Oben verspricht er noch, jeder könne alles in seinem Blog schreiben. Dann löscht er meinen Eintrag, der in diesem Screenshot noch auf Godfreys “Moderation“ wartet, dann aber umgehend gelöscht wird.

Im Blog mit dem großspurigen Untertitel “Serving the MH370 Community” treiben Richard Godfrey et. al. allerlei Unfug. Mit scharlatanesquen “Technical Papers” versuchen sie, Flugzeuge über Tausende von Kilometern anhand von WSPR-Logdaten zu orten. In unverantwortlicher Weise spielen sie mit den Hoffnungen von Hunderten von Angehörigen jener Passagiere, die beim Crash von Flug MH370 ums Leben kamen.

Während bisher keine seriöse technisch-wissenschaftliche Zeitschrift diesen schrägen Thesen Platz eingeräumt zu haben scheint, finden sie vor allem in der Yellow Press und beim Laienpublikum Anklang. Vorschlägen, die “Thesen” einem Peer-Review zu unterziehen, wollten die Autoren natürlich nicht nähertreten: Der mit viel Unwissenheit und beträchtlicher Eitelkeit mühsam aufgeblasene Ballon würde noch vor dem Abheben platzen. “Sie wissen nicht, was sie tun”, urteilte Physik-Nobelpreisträger und WSPR-Entwickler Prof. Joe Taylor, K1JT, über diese “verrückten” Experimente.

Hauptsächlich verbreiten Godfrey et al. ihre verdummenden “Thesen” über Godfreys Website. Ein Publikum, das etwas von Funkausbreitung, WSPR und bistatischem Radar verstehen würde, verwiese diese Thesen in einen Bereich, der nicht mehr in die Zuständigkeit der Physik, sondern in die der Sozialpsychologie fiele.
Die einzige Ausnahme, wenn es denn eine gibt, scheint der DARC, der Deutsche Amateur Radio Club, zu sein. Dessen Vorsitzender, Christian Entsfellner, DL3MBG, und seine Webseite machen kräftig Werbung für diesen unwissenschaftlichen Hokuspokus. Er sollte es besser wissen. Und ich bin mir sicher: Er weiß es besser. Das macht es alles – nur eben nicht besser.

“Radio DARC” – eine der Schleimtrompeten (S. Kracauer) des “Bundesverbandes” – überschlägt sich gar: “Die unglaubliche Geschichte – exklusiv auf Radio DARC! Die unglaubliche Geschichte – exklusiv auf Radio DARC!” [ab 39:35]

Auch der DARC scheint, wie Richard Godfrey selbst, eine ernsthafte technisch-wissenschaftliche Diskussion über dieses Thema mit allen Mitteln verhindern zu wollen. Godfrey behauptet sogar schamlos gegenüber einem Autor: “@Omar Ahmed, jeder kann sich an diesen Diskussionen beteiligen. Alles wird wie gewohnt auf dieser Website veröffentlicht. Es gibt nichts zu verbergen.” (am 22. März 2022 um 21:09 Uhr, siehe Screenshot oben).

Das ist eine Lüge.

Das Gegenteil ist der Fall: Eben nicht jeder kann sich mit Beiträgen an der Diskussion auf seiner Website beteiligen. Und nicht alles wird veröffentlicht. Schon gar nicht, “wie gewohnt – as usual“, und/oder wenn es sich um technisch-wissenschaftlich seriöse Beiträge handelt. Auch das zeigt der obige Screenshot des Blogs, aus dem u.a. folgender Eintrag nur kurz aufschien, um umgehend gelöscht zu werden:

Richard – auch dem neuen Paper entnehme ich keinen Beweis im technisch-wissenschaftlichen Sinne, dass aus den WSPR-Logdaten Aircraft Scatter über Tausende von Kilometern bestimmten Flugzeugen, darunter auch Hubschraubern, zugeordnet werden kann.
Meine Empfehlung: Suchen Sie sich eine technisch-wissenschaftlich orientierte Zeitschrift mit einer technisch kompetenten Redaktion. Veröffentlichen Sie dort Ihre Thesen und Beweise. Die CQ DL des DARC wäre ein Anfang, und man wird Ihnen sicher gerne behilflich sein. Vielleicht kann Ihr Manuskript auch einem Peer-Review unterzogen werden. Am Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR (ex-FGAN) gibt es genügend Experten und sogar Funkamateure, die Ihre Manuskripte bestimmt gerne begutachten.
Übrigens stimmt es nicht, dass auf Ihrer Website jeder einen Kommentar abgeben kann. Ganz im Gegenteil. Ich konnte (kann?) das nicht, und Sie haben mich beim DARC-Vorsitzenden verleumdet, ohne dabei eine einzige Zeile zur Physik zu verlieren. Die Tatsache, dass der DARC-Vorsitzende sofort über dieses Stöckchen gesprungen ist, sollte Ihnen den Schritt in die tatsächliche und wissenschaftlich überprüfende Öffentlichkeit erleichtern.
Ihre Bemühungen und Ihre Begeisterung in Ehren. Aber Sie sind auf dem falschen Dampfer.
73 Nils, DK8OK


Richard Godfreys unverantwortliche Tätigkeit ist eine Schande für alle Fachleute, die sich ernsthaft mit dem Thema “Funktechnik” beschäftigen. Und es ist höchst unethisch, mit den Hoffnungen der Menschen zu spielen. Dass der DARC das nicht nur mit allen Mitteln kräftig unterstützt, sondern sein 1. Vorsitzender, Christian Entsfellner, DL3MBG, sich dem Vernehmen nach sogar bei anderen Medien für eine Unterdrückung technisch-wissenschaftlicher Artikel zu diesem Thema einsetzen soll, ist ein weiterer trauriger Tiefpunkt des Vereinsfunks.

RTL-SDR Active Patch Antenna

Weather-proof: and this is only one of the benefits of this nice tool.

Since August 2021, the RTL-SDR Active Patch Antenna delights the community worldwide. It is small, yet highly efficient. With RTL-SDR Dongle and some software, it combines to a surprisingly high performance receiving post for INMARSAT, IRIDIUM (which I first used with a mobile phone 20 years ago on a tour through Mongolia and China with stunning quality), and GPS – all for just about 100 US-$.

Plug the USB stick into your PC, connect the patch antenna to the stick’s by a cable and set it on a flexible tripod (all contained in the set!), and the sky becomes open. In the screenshot below, I used the nuandRF to show at least half of the bandwidth of the antenna, because this SDR covers 60 MHz:

The 60MHz wide window of the nuand bladeRF SDR shows half of the bandwidth and sensitivity of the RTL-SDR Patch antenna. Caveat: With the bandwidth of the antenna being nearly 140MHz and the bandwidth of the SDR only ca. 60MHz, this screenshot still doesn’t show the complete performance of the antenna. The seemingly (sic!) reduced sensitivity at the lower and upper end of the signal/noise is due to the receiver, not the antenna!

Aero makes a good start with powerful signals and free software JAERO which can also run in multi instances to cover all the channels in parallel.

In the upper window you see the SDR GUI, namely free SDRC software. It shows some aero channels with their signal-to-noise radio, or SNR, achieved with the active patch antenna and the RTL-SDR dongle. The two windows at the bottom show the JAERO decoder in action on a 1200bps channel.

You may also set sails for some maritime experience with the std-C Decoder (full version: 55 US-$). It even visualizes e.g., buoys and areas (rectangle, circle and free format) a Open Street Map.

Top: a maritime satellite channel. Bottom: Safety Message for the marked area in the Gulf of Bengal, off the coast of Cuttack/India.

You may also receive the GPS C/A code signal on 1.575420GHz, and IRIDIUM on which John Bloom wrote the pageturner “Eccenctric Orbits – The Iridium Story“, which I can only highly recommend as a truly thrilling backgrounder. As low-orbiting satellites, the channel has to be handed over to another satellite after about nine minutes.

The RTL-SDR Active Patch Antenna is a great, little tool providing high SNRs at a small form factor of 17.5 x 17.5 cm. Its low noise amplifier (powered via bias tee from the SDR stick) together with the SAW filter to suppress any signals outside its passband from 1.525 to 1.660GHz shows unsurpassed performance at this price tag. It is a must, and absolutely a no-brainer. Did you miss a large suction cup to mount it on your window? Wait a minute – it is also included in the turnkey package …

WSPR & Propagation [MH370] – an Experiment

Completely unintentionally, my last blog on WSPR and MH370 had led to more of a social psychology experiment than a technical science discussion. I expressed my doubts whether it is possible to recognize aircraft scatter from the historical WSPR data by “unusual signal changes” without essential knowledge of further circumstances.
As a reminder: WSPR works with weak transmission power at modest antennas in a rhythm of 110.6 seconds. Apparently this average value is noted and made available as SNR at the receivers.

I objected that practically all other influences on the signal on its way from the transmitter to the receiver (“channel”, with refractions both at the dynamically in three dimension, plus density, changing ionosphere and at the ground) exceed those effects by far, as they are to be expected by airplane scatter. I proved this with 3 x 10’000 level data and 30+ Doppler tracks.

The main proponent of the theory, that the proof is possible against all those odds, reacted with a juicy complaint to the German amateur radio association DARC, in which he argued exclusively personally, but not technically-scientifically. A behavior even more bizarre than trying to prove his actual thesis. The DARC immediately jumped over the stick held out to it, and published few hours later – apparently without or against better knowledge – a sweetish-mendacious “press release“, in which a so far not by technical-scientific papers noticed employee praised that as only beatifying truth.

[Auf Wunsch einiger deutschsprachiger Leser erfolgt in einem weiteren Blog eine Erläuterung dazu.]

WSPR vs. high-resolution data

For all those, however, who are interested in technical contexts, this blog answers a still open question from my last blog:

  • What is the smoothing/generalizing influence of the evaluation of mean values over 110 seconds – which is how the WSPR logbook is supposed to work – on the mapping of the actual signal changes?

Let’s simply test it
For this purpose I have analyzed on September 22nd, 2021 with the professional SDR Winradio Sigma between 07:00 and 12:00 UTC the broadcasting station CRI Kashi, which transmits continuously on 17’490 kHz with 500 kW towards Europe – 5’079 km, two hops. My antenna is a professional active vertical dipole antenna with 2 x 5 m long legs, namely MD-300DX.

With the software SDRC 17’930 level values were noted in dBm/Hz, every second. The FFT analysis was performed with a high-sensitivity resolution of 0.0122 Hz, resulting in a process gain of 53.1 dB compared to the data from WSPR, measured in a 2’500 Hz wide channel. Assuming the carrier power of the transmitter to be 250 kW and the gain of the transmitting antenna HR4/4/.5 to be typically 21 dBi, this results in an additional gain of 47 dB compared to a WSPR transmitter of 5 W on a dipole, which is already strong by its standards. Thus, the total gain of this experiment is 100 dB compared to a WSPR signal. If we assume that signals with SNRs between -20 and -30 dB can still be evaluated, the gain is still a robust 70 to 80 dB. Thus, if aircraft scatter were to be detected on a WSPR signal, it would be even more striking with this factor.

The spectrogram of the five hours’ recording see below, followed by an explanation of the annotations (as with all screenshots: double-click to get the original resolution):

Kashi’s carrier over 5 hours, shown within a window of ±50Hz and a resolution bandwidth of 0.0122Hz at an dynamic range of 90 dB. Explanation see the following text.

The spectrogram reveals a couple of different strong influences to level and frequency of the carrier. Most prominent is the Doppler shift by a moving ionosphere, plus the split-up into o- and x-rays due to the magnetionic character of the ionosphere. You may simulate it with PropLab 3.1, but only in 3D mode. Aircraft Doppler is very weak. It has been verified as such by a different spectrogram with better time resolution, not shown here. You see also some Doppler from meteorite’s plasma in the vicinity of the carrier.

The level of the carrier can be seen from the following screenshot at a time resolution of 1 second, enriched with some statistical data:

Levels over 5 hours. Mean = -44.02 dBm, Standard Deviation 7.872, Range 58.81 dBm. Max/min: -21.97 dBm/-80.78 dBm

The next screenshot shows the whole 17’930 datapoints, split up into consecutive groups of 110 each. This should simulate the the 110.6 seconds which the WSPR logbook boils down to one SNR value plus on “drift” value. To read this contour map:

Vertically you see 163 columns. Each column contains the levels 1 … 110, and 110 x 163 = 17’930 total level values. For the first time, you can see here the dynamic within a column of 110 values each.

Contour diagram, showing all 17’930 level data, grouped to 163 blocks of 110 data points each.

So far, we retained the level information of all 17’930 data points. What happens if WSPR boils them down to chunks of 110 seconds only? This question answers the next screenshot:

What is lost by boiling down the 17’930 level values at 1 second’s distance to 163 chunks of the mean of 110 values? This screenshot shows the answer.

If it still isn’t understood that information which simply are not palpable in the 110-seconds’ chunk cannot be “interpreted” as this or that, a zoom-in must convince you:

Same as above, but zoomed into. WSPR logbook will keep only the Chunks. So all information has to be derived from just the red line! Imagine that you don’t have any more information – no “Raw”, no “Spectrogram”.

Looking at the both screenshots above: are you still sure to see any faint details (refer to spectrogram on top of this blog) like any Aircraft Doppler just from the chunks? You have also seen that the “drift”, shown in the WSPR logbook, may have manifold sources, ionospheric Doppler prevailing.

Stanag 4285 & PSKSounder – a better mode

There, of course, is a way out of this dilemma: since many years free PSKSounder provides an excellent tool to extract many more information from STANAG 4285 signals, see the following screenshot:

PSKSounder shows relative “time of flight” of a Stanag 4285 signal. Here with FUV, French Navy in Jibuti. You see that the structure of the spectrogram of the signal at the right has it source in two strong and different paths of the signal. Their times of arrival differ by about one millisecond. This procedure is very sensitive and is also used to reliably reveal meteorites and – aircraft!

Finally two things: The path between two stations does not always have to be exactly reversible – that is, if two stations are equipped exactly the same, it is very likely that a different signal will be detected in each case. And if the black box of MH370 should indeed be found in the area supposedly designated by WSPR, it is due to many things, but certainly last of all to WSPR.

After which methods it might be tried nevertheless, one can read already now in Grete De Francesco’s “The Power of the Charlatan”, Yale University Press, New Haven/USA, 1939.

MH370 and WSPR: Aircraft Scatter on HF – A Critical Review

Some articles had been published stating that processing of WSPR logs can assist in reconstructing the route of an aircraft (i.e., MH370) by a method known as bistatic radar. Nils Schiffhauer, DK8OK, has some doubts. Read his reasoning below.

Some Doppler traces in vicinity of the carrier of China Radio International from Xian-Xianyang, broadcasting with 500kW (250kW carrier) on a curtain array antenna providing nearly 25dBi gain towards 190°. More on the lower than on the upper sideband you see some aircraft Doppler traces at distances of 8Hz to 17Hz (LSB), corresponding to a relative velocity of the aircraft from about 200 to 600 km/h. Frequency resolution: 0.0047 Hz.

Again and again, efforts by radio amateurs make the rounds to have identified the crash site of MH370, for example, on the basis of the evaluation of WSPR logs. For this purpose, they primarily evaluate “unusual” level changes in the WSPR logs.
The fact that RF signals are scattered by the metal hull of aircraft is nothing new. The best way to see this effect is to look at the Doppler tracks that form at a certain distance from the actual carrier frequency of the transmitter. This is based on the theory of bistatic radar (see for example “Bistatic Radar” by Nicholas J. Willis, Raleigh NC, 1995).

Aircraft Scatter: Bistatic Radar

This concept has been used worldwide for decades, in the HF range primarily in the form of various over-the-horizon (OTH) radars.
In principle, a signal with known properties (amplitude, waveform …) is transmitted and received again after having passed through the “channel”. Comparing the transmitted signal with the received signal, the properties of the channel can be deduced.
Professional systems with powerful transmitters, beam antennas with high gain and signals with precise characteristics, whose scattering is evaluated with highly specialized algorithms, allow the detection of even small aircraft and ships in rolling seas. Intelligent evaluation includes the extensive elimination of interference factors, from sea clutter to changes in the ionosphere. These also have a considerable influence on the received signal – including amplitude and frequency (Doppler and split-up into x and o rays).

WSPR: A challenging mode

Transferring this technology to the evaluation of level and frequency of WSPR signals faces a couple of challenges:

  • The effective transmit power of WSPR signals is only roughly known at best, but in terms of magnitude it is at least 50 dB below that of professional OTH equipment.
  • The quality of the transmitted signal in terms of frequency stability, noise and possible amplitude changes (power supply!) is not known.
  • The changes of the ionosphere (attenuation, Doppler, multipath …) is not known.
  • The waveform WSPR, as well suited as it is for QRP communications, has not been developed for its use as bistatic radar.

All previous evaluations, especially in connection with flight MH370, are based primarily on evaluations of level changes, measured as just one mean value of a 110 seconds long transmission. It has been postulated that aircraft scatter increases the overall level of the signal. (“Drift” seems not to be a proxy for “Doppler”, see below). A possible evaluation of the Doppler shift fails so far largely because of the data situation. This also prevents the inclusion of the current state of the ionosphere and its local fine structure. Catching up ray tracing – moreover only two-dimensional! – can by no means compensate this disadvantage.

Correlation vs. Causality

However, far-reaching expectations are attached to the existing and modest material [Sensational new finding for MH370 flightpath], which in my opinion are already epistemologically, but also technically on feet of clay. This is like one can make Mozart’s “Kleine Nachtmusik” sound out of pure noise by suitable filtering. This also happens to high-ranking scientists, for example, when they detect neuronal correlates in the brain of a dead salmon and erroneously conclude that it is solving mathematical problems … there has been everything. Correlation doesn’t always mean causality.

My doubts about using WSPR logs for the purpose of locating aircraft are based on two main points:

  • We know little to nothing about the actual state of the fine structure of the ionosphere, which primarily affects the signal.
  • We have only guesses about the extent to which (amplitude, Doppler …) an object flying in an unknown direction scatters the signal (type, height, direction, speed …).

Furthermore, raytracing in those examples calculates with unusually low elevation angle of under 3°. PropLab 3.1 [most recent build #43] sees the main elevation of, e.g., a vertical dipole at more than 20°.

Just as an aside, when the central paper on “WSPRnet Propagation Technical Analysis” states, “Flat ice or calm ocean provide the best surface’s for WSPRnet signal reflection.”, the opposite is true, at least as far as the conductivity of ice is concerned. It has the worst conductivity and thus reflectivity of all soils on the earth’s surface and, at 10-4 S/m, is in last place in this respect according to ITU-R P.527-4.

HF Scatter: What the Experts say

The relevant literature on HF radar deals with such central matters as radar cross section (which defines the return power of an modeled object, which can vary by several 10 dB under different circumstances), scatter in Rayleigh and Mie regions (dependence on wavelengths and dimensions of the object), and inhomogeneities of different layers of the ionosphere – concepts of which most previous studies on the subject of “WSPR and MH370” make sparse use at best.
I do not want to bore now with long-tongued recounting of these things, but to pick out thesis-like only some points from the NATO paper HF-OTH Skywave Radar for Missile Detection” as a quotation (bolded by me):

* We must deal with heavy propagation losses due to the very long travelling distances as well as strong absorption losses mainly due to the D layer of the ionosphere. The whole loss contribution can be up to 100-150 dB.

* The apparently simple propagation mechanism hides the complexity of the ionosphere structure. This implies a challenging target localization that could be achieved by a smart system calibration combined with a three dimensional reconstruction of the signal path through the ionosphere.

* OTH radar system functionalities are strongly dependent on the ionosphere and on the environment noise level that means geographically dependent performances. Accordingly the radar siting represents one of the key choices.

* High values of peak power are necessary in such systems to deal with strong losses.

* It is essential a simulative approach that can provide a predicted radar cross section variability as a function of the operating frequency and of the aspect angles that are unusual for ordinary radar systems.

Certainly, these military requirements do not have to be transferred 1:1 to our more semi-professional approach. Nevertheless, they set such narrow limits to even our modest approach that their meaningful application threatens to disappear almost completely in fading and noise.

Amateur’s Choice: +70 dB – and more

In order to verify at least some basic assumptions in practice, I have conducted a series of investigations on carriers of shortwave broadcast transmitters. These have several key advantages over WSPR:

  • They provide a known signal in terms of frequency stability and amplitude.
  • Their effective transmit power is about 70 dB higher than that of WSPR transmitters.
  • Each station transmits continuously for at least 30 minutes, allowing relatively large integration times to improve the frequency resolution (up to 0.005 Hz, or adding another 57 dB in a 2’500 Hz channel) and thus the sensitivity for detecting the Doppler signals.
  • This setup allows a clear separation of original signal (via ionosphere) and aircraft scatter by shape and frequency. This eliminates what I consider to be the biggest unknown of the WSPR approach.

However, there is one drawback: only between 0 and 10% of even these strong transmitters can be used to detect Doppler traces from aircraft. Only with a smart match of frequency, time, flightpath, propagation … you will have some success.

Let me pick a typical example from a series of experiments – all with similar outcomes. The Chinese transmitter at Xian is received with 500 kW (carrier: 250 kW) on a GPS-locked SDR Elad FDM-S3. Its carrier on 17’530 kHz was first displayed under magnifier of two software, namely PSKOV (screenshot on top of this blog, for a first introduction click here) with 0.005Hz resolution, and SDR software SDRC with 0.39 Hz resolution, see screenshot below. The latter provides the numerical output used in the following post-processing.

Situation with software SDRC, compared to the PSKOV-screenshot at top of this blog.

Needle in a Haystack?

The next step is to answer the following question: Is it possible to detect the influence of the Doppler tracks in the overall signal? After all, this is the method that is tried using WSPR.
For this I first divide the total signal of 100 Hz width into three channels: Carrier, Doppler and Noise, see below. The Doppler signals are clearly visible, the respective correlation coefficients between the channels “Carrier”, “Doppler” and “Noise” are all well below 0.1, which shows the independence of the three different signals from each other and their separation. Mean Level of Carrier is -59.1 dBm, standard deviation 5.71. Mean Level of Noise is -108 dBm, standard deviation 4.5.

Signal levels over 10’000 seconds for all three channels.

In the following step, I sum up the channels “Carrier” and “Doppler” (de-logarithmize the dBm values in mW, addition, re-logarithmize the mW values to dBm).

If I now compare the data “Sum level of Carrier and Doppler” with the “Carrier”, the correlation diagram shows a near-complete agreement between both data sets – see screenshot below:

Correlation diagram fo Carrier and Carrier+Doppler (blue marks) shows only miniscule differences from 100% identity (red line).

Are rounding errors the reason for those miniscule differences? No, as we see in the following screenshot where you can see that the Doppler trace increases the signal of the carrier by 0.2 dB to 0.3 dB at most, except for a single exception: 0.6 dB.

But these values are almost completely lost in the overall signal with its standard deviation of 5.71, if they are not anyway below the measurement accuracy of many SDRs and their software.

The screenshot below draws the difference between [Carrier+Doppler] and [Doppler] – values left Y-scale – together with the original Doppler signal – right Y-scale. Judge for yourself …

The Doppler traces are practically lost in the fluctuations of the carrier signal.

For the complete overwiew of the steps see the workflow below:

Workflow, done with Elad FDM-S3, SDRC, MatLab R2021a.

WSPR & Aircraft Scatter? I have my doubts.

We started with the challenge to see some signal enhancement by scattering from aircraft in WSPR logs. Those should lead to “unusual” changes within the signal. A WSPR transmission lasts for 110.6 seconds and delivers just one mean SNR value representing his time (plus drift with a resolution of 1 Hz only).

It was suggested that from these signal levels (and drift data) aircraft scatter can be derived. This had been tried to underpin with 2-dimensional ray-tracing propagation simulation, based on statistical, rather then real data.

I tested those assumption with 10’000 level data at one second resolution, +70 dB in transmitting power, added by a few 10 dB of processing power. Doppler traces from 30+ aircraft had been analyzed. Backed by this, it can be stated:

  • On HF over longer paths (from two hops/with multipath propagation), usual aircraft scatter has nearly no effect on the overall reception level. Without prior knowledge, it is hard, or even impossible, to conclude aircraft scatter from the sum signal.
  • Doppler effects occure in the region of about 5 Hz to 20 Hz and don’t coincide with the much lower “drift”, I saw in the WSPR logs.
  • The power of a typical WSPR setup is many ten dBs down to what it should be to reliably identify aircraft scatter.
  • We usually know near nothing about the transmitter’s and receiver’s site – power, noise, drift etc.
  • We know near nothing about the channel (propagation) at the refracting points. This makes it difficult to separate different effects from each other, of which aircraft scatter is just a minor one, with multipath fading being the absolutely prevailing one.
  • The statistical population/resolution of the data one gets from the WSPR logs is too small (due to the 110 seconds) to apply robust statistical methods to cope for a dynamic environment.
  • The simulation capabilities of PropLab are not sufficient for such long-range statements due to, for the given case, poor temporal and spatial resolution of the usable ionospheric data. In addition, the simulation with PropLab was, to put it mildly, not optimally implemented – 2D instead of 3D, airy assumptions about the angle of incidence of the signal, and wrong assumption about ground conductivity.

My final conviction is: the detection of aircraft scatter and its assignment to specific flights from WSPR data is far more wishful thinking than reality. Only with considerable prior knowledge and using other data sources as well as possible coincidences these statements can be explained. WSPR in itself is not likely to contribute to this.
There are far more RF signals that are far better suited for this purpose for a variety of reasons. Trump, however, would be digital beacon project, whose waveform is suitable for also qualitative studies of the propagation path. Here, a private initiative seems to be active, after amateur radio clubs continue to stick to analogue technology (NCDXF, once meritorious).

Just a quick answer …

… to a question, I have been asked:

Q: “WSPR is sampling SNR for 110 seconds, boiling this down to one value. The resolution of your approach is one second. Does this influence the results?”

A: “Surely – higher resolution = more details, better insights!”

Q: “Can you show me?”

A: “I warn curious, but that you are, gladly!”

The screenshot below offers an answer to the question: “What does the WSPR log see, which only notes the sum voltage and also this only as an average value (?) – and also this not every second, but in intervals of 110.6 seconds?” Because with WSPR one has only this one sum value. For this purpose, exactly this situation was simulated with the originally good 10,000 data values collected every second and these were divided into groups of 110 seconds each, whose mean value was formed. This then corresponds to the SNR value in the WSPR logs.I boiled down my data of “Carrier+Doppler” and “Doppler” to 91 groups of 110 seconds each, and then I calculated the mean values of each group. In my view that should match the SNR values of WSPR (“Carrier+Doppler”).

Sum level and Doppler level. Allegedly, one should be able to conclude from “unusual” sum levels to aircraft Doppler. Which without prior knowledge leads predominantly to false-positive (FP) and false-negative (FN) results, of which only some are entered here. Rolling the dice gives a better result.

I then calculated the 95% confidence interval from these largely normally distributed mean values and restricted the plot in the above screenshot to those values that lie above the upper limit of this confidence interval of 58.02 dBm. These are “unusual” values in my eyes, although this is only a reasonable guess, because the authors do not specify further what they mean by “unusual”. The course of the values “Carrier+Doppler” is scaled on the left Y-axis, from -58 dBm to -54 dBm.
According to theory, a Doppler signal should now be lurking behind each of these values above -58 dBm, at least in the “unusual” peaks. Is this true? To check this, I plotted the corresponding processed Doppler levels in the same diagram, scaling on the right Y-axis, -110 dBm to -98 dBm.
Already a first look shows that the connection of both curves is rather random. With FP like “false positive” I marked for clarification at least some of those positions, where due to the “unusual” sum signal an aircraft Doppler would have been expected – but was not present. With FN are marked, vice versa, some of the positions, where there was a Doppler signal, but no “unusual” course of the sum level indicated it. A clear assignment “unusual sum signal -> aircraft Doppler” is therefore unlikely.

Comments welcome: dk8ok at gmx.net

P.S.

Oh, yeah, we had some comment! Richard Godfrey rebuked my technical-scientific based criticism on his website (“Serving the MH370 Global community”), which explicitly invites discussion, with the following “arguments”:

“You are not welcome on this blog!You were thrown out of the German Radio Amateur Club (DARC) in 1992. Despite 3 appeals at regional and national level as well as in court, you are still excluded from membership 29 years later. There are very good reasons for this. …I have complained to Christian Entsfellner DL3MBG, the current Chairman of DARC, about your demands to protest against my work and that of Dr. Robert Westphal (DJ4FF) officially on the DARC website regarding MH370 and WSPRnet.Your paper is plain wrong and your arguments are misplaced.I suggest you go elsewhere as I am sure there are other MH370 websites who will welcome the likes of you. Und Tschüss!”

” Ambition should be made from sterner stuff.” [Shakespeare, Julius Caesar, Act III]

I like to recommend a website where you find much ado about sterner stuff concerning MH370 and WSPR:
MH370 and Other Investigations – Following the Data Towards Discovery.

Ahoy! Decoding eight GMDSS Channels in a Convoy

Decoding all GMDSS channels at once: Black Cat System’s groundbreaking GMDSS Decoder.

Chris Smolinski, W3HFU, did it again: after his multi-channel attack to ALE, he now offers this highly innovative concept also for GMDSS – Black Cat GMDSS. In addition to an extraordinary sensitive decoder, it also includes smart processing of the data – from looking up vessel’s complete data from ITU’s Ship Station List (internet connection needed) to saving all data to a fully-fledged database. Welcome aboard! Now let’s set sail!

3000+ Messages a Day – received on HF

The Global Maritime Distress and Safety System is a system of different maritime communications tools on frequencies ranging from as low as 424kHz [NAVTEX] over HF and VHF up to satellite channels in the GHz region. This blog entry focus on Black Cat GMDSS decoder, hence on HF. There, the six main channels range from 2MHz to 16MHz. Reception of both, Coastal Stations and vessels, is from around the world. In this case from Vestmannaeyjar Radio in Iceland to Cape Town Radio in South Africa, and from Valparaiso Playo Ancha Radio in Chile to Taupo Maritime Radio in New Zealand. You may hear vessels of each and every kind, from small ones for pleasure to the biggest oil tankers, and all over the world. Monitoring on all six main channels in parallel, often raises 3000+ messages a day!

Robust FSK mode

Transmission is done in 2-FSK with 170Hz shift and at speed of 100Bd. Waveform is ‘kind of SITOR-B, repeating each character twice with a 400ms spread to enhance proper decoding under adverse propagation (Rec. ITU-R M.493-11). To establish a call, each station has been assigned to an unique MMSI, or Maritime Mobile Security Identity number consisting of now nine digits, in future 10 digits. MMSIs starting with 00 denote a Coastal Station, e.g., 004123100 for Guangzhou Radio/China. There is a set of 127 symbols, with the first numbers 00 to 99 representing numbers, and each of the remaining number specific situations like “110” denoting “Man over board”. The software has to look up those source-coded messages in a codebook to print a readable message, giving some sense.

Smart coding

One message is about 6.4 seconds long. it starts with a short dot-pattern/phasing sequence for automatic tuning, followed by the content. In this live example, JRCC Australia (MMSI 003669991) is calling Merchant Oil tanker Signal Maya (MMSI 248410000) on 12577kHz at 15:59:43 UTC on November 21, 2021.
There are transmitted 23 groups (“Symbols”) in GMDSS :

  • 120 120 021 007 061 000 000 108 000 050 030 000 010 118 126 126 126 126 126 126 126 122 111

and decoded as follows:

  • 120 120 -> Format
  • 021 007 061 000 000 -> Address – MMSI of called station
  • 108 -> Category
  • 000 050 030 000 010 -> Self MMSI – MMSI of calling station
  • 118 126 -> first and second [none in this case, “idling”] telecommand message
  • 126 126 126 -> frequency message [none in this case, “idling”]
  • 126 126 122 -> end of message
  • 111 -> error-check character [ECC]
  • After a look-up in the codebook this turns into:
  • Format: Individual call
  • Address [to]: 210761000
  • Category: Safety
  • Self MMSI [from]: 005030001
  • First telecommand: Test

… even smarter decoding!

Still not much enlightment. But BCS-GMDSS is at your service. It looks up all the cryptic numbers at different sources, even tapping official ITU webpage to enrich the vessel’s MMSI with its stunning mutltitude of information. Wrapping it up, decoding and looking-up in an internal codebook (Coastal Station) as well as in ITU sources (vessels), the above mentioned 23 symbols come out in full glory reading:

[2021-11-21 14:59:43] 12577
Symbols: 120 120 021 007 061 000 000 108 000 050 030 000 010 118 126 126 126 126 126 126 126 122 111
Self MMSI: 005030001 – Australia – JRCC AUSTRALIA 26 20′ 48″ S 120 33′ 52″ E 13669 km, 92 deg
Address: 210761000 – Cyprus
Ship: SALT LAKE CITY | Callsign: C4DS2 | MMSI: 210761000 | Cyprus (Republic of) (CYP) | Vessel ID: 9314129 | EPIRB: BE1 | 06/12/2017
Class: Merchant | Bulk carrier | | 89076 tons | 26 persons | INMARSAT C MINI M INMARSAT M VHF DSC | 24 hr service
Owner: NOBEL NAVIGATION CO LTD POB 50132 LIMASSOL CYPRUS
Misc: Former Name: THALASSINI NIKI | | EPIRB ID: 210761000 | | Telephone Bands: STUV | AAIC: GR14 | | CO | |
Format: Individual call Category: Safety First telecommand: Test

As you have seen, I already mixed some theory with some practice – as you know me.

Now for some features of the software, plus some hints to make the most out of it.

Some basics, you must be tuned to

BCS-GMDSS offers up to 8 channels in parallel which by default are set to the main six GMDSS channels plus two with only rarely traffic observed, also on 2MHz. Those channels are fed by a SDR, ideally covering the whole range from 2MHz to 17MHz, alias-free. In this range you have to place the up to eight channels, RX1 … RX8, and have their output set to VAC1 … VAC8. The inputs of the decoder have to match those VAC numbers – see screenshot.

Here, six GMDSS channels have been set with SDRC software, controlling a Winradio Sigma SDR at 20MHz bandwidth.

Take some care to think about mode, tuned frequency and audio frequencies, and bandwidth. Mode can be USB, CW-U or FSK, whatever your SDR’s software offers. It is, however, mandatory that the center frequency of the audio output must match the centre frequency of the input of the decoder! Otherwise there will be no decoding.

I am using free SDRC software by Simon Brown, G4ELI, easily providing all eight channels via VAC software. I am using CW-U and a bandwidth of 400Hz, giving some room for stations which might deviate by some 10Hz from the assigned channel – the decoder automatically compensates for this. With this setup (see screenshots below), the frequency readout shows the assigned channels, plus centre frequencies of decoder and receiver are matching (here 1700Hz, as ITU recommends). The bandwidth offers a good balance of SNR and tolerance for stations with a slight offset. Your mileage may vary in some aspects, e.g., you may prefer SSB-USB mode, or your software has a BFO if you use CW …
You may also use the wrong sideband (LSB instead of USB) with your receiver – but than you just have to tick “Invert” in the decoder’s Setting menu as it then changes Mark and Space frequencies.

Center frequency set to 1700Hz, low to 1500Hz, High to 1900Hz – resulting in a bandwidth of 400Hz. The signal of Finisterre Radio on 8414,5kHz matches these values.
With center frequency of the audio output (1700Hz) and center frequency of the decoder (1700Hz) matching, a signal falls into both passbands – that of the receiver on the right side with spectrum and spectrogram, and that of the decocoder on the left with spectrum, amplitude and also the Setup menu.

Order! How to cruise through this Ocean of Messages

BCS-GMDSS cleverly combines a most powerful decoder with some extras to calm the rogue waves of decoded information. First, you may reduce (or extend) the degree of information you fetch form the ITU page: Edit -> Settings -> MMSI Lookup. It is very interesting to see the maximum of data (“Most Details”), but with everyday’s monitoring just “Basic” or “Detailed” may run the show. This creenshot is showing the differences:

Five different depth of data output: from “Details: None” to “Details: Most Details” – with all the same audio being decoded.

The second step is to distinguish the vessels from the coastal stations by color. I set the latter ones to show up in blue:

Here, messages from Coastal Stations are printed in blue (Edit -> Highlight Coastal Stations, set color).

Next, BCS-GMDSS offers a Coastal Station’s database. It is a real database which, e.g., each column can be sorted. In the screenshot below, I had sorted them according to their total messages received. Then “Yusa Radio” has been double-clicked to inspect the timestamps of reception:

Coastal Station do have an extra porthole offering some interesting statistics. Each column can be sorted, and a double-click reveals timestamps of one station.

The “Loggings Database Search” is like a supertanker, containing all your logs which can be sorted by a double-click, plus being queried for each column, also combining different criteria. This is the most powerful database any GMDSS decoder has on board. See screenshot below for just one example:

The whole log of 12’590 entries had been queried for messages from Coastal Stations on 2187.5kHz on November 21, 2021 for 24 hours. This answer is of course just a small part of the whole reply from the database.

Addendum: Where are they cruising?

The location of most Coastal stations is openly available, and their geographical coordinates are internally looked up by the software – even calculation of the distances to your location (Edit -> Settings -> Latitude:/Longitude:) is done automatically.
But where are the vessels cruising? They only rarely transmit their location in GMDSS on HF. But if they have an AIS, or Automatic Identification System, you have a fair chance to get the actual location. This system comes in two tastes: AIS and LRTI, or Long Range Identification and Tracking. AIS is using VHF. Propagation restricts the range to some ten kilometers. LRTI is using satellite (INMARSAT). There are some webpages where you get at least AIS for free – just to mention VesselFinder, VesselTracker and MarineTraffic. Their business model is to offer subscriptions for one year at a price of about 1’200 US-$ for LRTI (satellite) data, aimed mainly to the professionals. But most of those companies offer (limited) access to their AIS data for free. The two screenshots below show the difference.

Scattered with vessels: VesselFinder’s professional version listen to all seven oceans via satellite, but offers …
… free acces to AIS data (VHF) which is due to propagation and volunteers feeding this net to those coastal regions.

The example above, bulk carrier Salt Lake City, is only availabe on LRIT. So free data are about one week old. Nevertheless, you get at least a clue where the ship had been. And if time plays no role, just look it up exactly this week later …

For free, we get only a weeks’s old satellite information. At least we can can see the bulk carrier had started from Manila on November 14, heading to Abbot Point in Australia where it is expected on November 29. A rough estimate is that she may have been cruising through the Banda Sea at the time of being called by JRCC Australia.

If you have received the following message, you are lucky:

[2021-11-22 17:02:38] 2187.5
Self MMSI: 229375000 – Malta
Ship: CMA CGM FORT DESAIX | 9HA5478 | 229375000 | MLT | MLT | 9400174 | 229375000 | 04/08/2021
Address: 002275300 – France – MRCC CORSEN 48 40′ 60″ N 2 19′ 0″ W 947 km, 252 deg
Format: Individual call Category: Safety First telecommand: Test

This vessel is covered by AIS (VHF) with its up-to-date data available for free at VesselFinder.

Multi-channel ALE Decoder: Listing and Logging

As if by magic, a file [invoked, marked yellow] completes the decoded messages to a complete and easily readable log. ALE callsign “111111” had no entry in the file, therefore this unidentified USAF aircraft cannot be solved.

Chris Smolinski’s Black Cat Systems ALE Decoder has changed monitoring ALE messages which are widely used onf HF to provide an automatic link establishment. It has set the standard not only by its unsurpassed sensitivity and the option to decode up to 24 channels in parallel, but also with its look-up table for “translating” cryptic ALE callsigns into stations and locations of flesh and blood. Tahnks to this, the usual decoded message of just

  • 7527.0 [Frequency in kHz] USB [mode] 2021-11-10 22:54:24 [date/time] 16 [BER] TO TSC TIS K62

turns into:

  • 7527.0 USB 2021-11-10 22:54:24 16
    TO TSC COTHEN Technical Service Center Orlando FL USA
    TIS K62 USGC MH-65D/E Short Range Recovery Helicopter Dolphin #6562 USA

This blog entry provides a description of the system as well as a list of 3’200+ ALE callsigns as a First Aid Kit.

How Callsigns come into Life

This feature is a major achievement in DXing. And it is, too, that innovative that we have to set our sails into unchartered sea. [Do you remember the completely blank OCEAN-CHART. in Lewis Caroll’s “The Hunting of the Snark” from 1876? You are here!]

The general idea of the software is to look-up each decoded callsign in a list of tab-separated information where you already had collected metadata like organization, station, location, country – anything you consider important.
The software then looks up each callsign – as above TSC and K62 -, introduces all the information in a neat way and prints it all together in the window. Even more, as the software automatically fills a logfile with all this for later inspection, edition and further processing by spreadsheet or database. Smart! And unique!

The callsigns’ document and its quality (extent, reliability, consistency …), of course, plays a pivotal role, see following illustration – shit in, shit out.

Information is circling from your Reference Database into the decoder’s look-up files (folder “ale_callsigns”) and back.

Whatever format your Reference Database may have, it will and must put out a simple tab-separated textfile.

It helps if you think of different type of data (organization, location, country …) as of different fields or cells, each separated by a TAB from each other – see an example with just one entry below.
All data fenced in by TAB can contain arbitrary characters, such as spaces, brackets, commas etc.

ALE CallOrganizationNameLocationTypeITU
HNCUSCGHarriet LanePortsmouth VAWMEC-903USA
Each cell/field is separated by a TAB. “Harriet” and “Lane” are separated by just a blank and as a result handled as one cell/field “Harriet Lane”.

Different output Formats for different Tastes

The decoder may present the same decoded message plus the same information from your callsign file in different ways, controlled by the “Settings” menu of the decoder:

Let us now decline the different Message Formats for a simple message of LNT calling J10 on November 6th, 2021 at 22:19:59 UTC, with data from “ale_callsigns”, see lines 16 to 18 :

Same message and same decode, but different formats and different log entries as well.

The sources for e.g., line 42 are marked in colors:

Divide and conquer

The look-up table(s) must be saved in a directory called “ale_callsigns” (lower case!) in the Documents directory for your user account.

The look-up table must be saved in the Documents directory for your user account.

Above you see not only one callsigns’ file, but many. There is a reason for that: If you have a large callsign file, undoubtedly some one and the same callsign will be valid for two or several stations. If the software detects this case, it prints (original decoded message):

  • 03 5732.0 USB 2021-11-10 22:29:03 31 TWAS J51 Ambiguous – multiple entries

This is because the list contains (in this case) two entries under callsign J51, namely:

  • J51 Royal Moroccan Armed Forces MRC
  • J51 USGC MH-60T Medium Range Helicopter #6051 USA

You can evade this ambiguity by defining different jobs with matching callsigns lists. If you want to check the channels of USCG/COTHEN, you should query your database for USCG only, save this set and invoke just this reduced set of callsigns instead of the complete bunch – divide et impera. This technique in most cases reduces the problem or even avoids it at all.
There maybe also the effect of a “false positive”: if a callsign doubles on two different stations, but you have listed only one under this callsign, being this the wrong one for the given case.

Basic Reference List: Database or Spreadsheet

I keep my data in a very simple FileMaker database with each entry carrying an individual number ALE_ref.

Example for one entry in my FileMaker database

Then you can query the list: “Tell me all USCG entries located in Alaska!”, getting this window out of your database. This must be exported as TAB-separated file (“USCG_ALS”) and put into the “ale_callsigns” folder of your “Documents” directory.

Result after asking for all USCG entries, located in Alaska.

Of course, you may use any type of spreadsheet and/or database.

You can see the content of folder “ale_callsigns” in the dropdown menu “Callsigns” of the decoder. There you have the choice to select one, two or many files or even “all”.

Under “Callsigns” there are listed all available callsigns files. Here I choose file “Full.tab” with 3175 entries of which 2956 are unique – as the decoder tells you under tab ” Channel 1″.

Callsigns: A First Aid Kit, 3’000+ entries

To become a bit acquainted with this new function, I prepared a list of callsigns containing only very few basic data. It must, of course, contain the callsign for looking up. I then provided fields for the organziation (USCG), the station itself, its location and the ITU 3-letter code. All fields/cells mut be separated by a TAB. For each field which is left empty (i.e., if you don’t know the location), you must insert a TAB instead. Otherwise, the other data may be wrongly allocated in your log. I also tried to keep a balance of streamlined data and the obvious desire not to have be a Rear Admiral of the Navy to understand all the acronyms. The list works perfect for the decoder, plus as sink and as source for your by far more flexible reference database/spreadsheet.

I plan to extend the list as well as to correct the mistakes. Your support is welcome!

The list is a first approach in format and content. It surely works fine. As all work in this field, it combines information from many different sources, contributors to UDXF must be named first. The list is also flavored with my own monitoring log of more than 11000 entries, being all different in call/frequency. In addition, there is a lot of information around in the web – surprisingly often from the organizations themselves, but also from flight spotters, vessel spotters etc. I am sure that all information used is “open”, as otherwise I couldn’t had no access to it … got it?

You can download the zipped list here:

If this doesn’t work, drop me a line under dk8ok_at_gmx.net.

Decoding ADS-B with free QIRX software

QIRX’ dashboard, decoding ADS-B: in the middle you see spectrum and spectrogram (“waterfall”) of the ADS-B signals. The window at the bottom lists alls received aircraft with additional data, whereas the top window places them onto a map.

In the last two blog entries, I took a look at the DAB capabilities of free software QIRX by Clem Schmidt, DF9GI, from Frankfurt. It directly works with RTL-SDR, Airspy and RSP2 SDRs. I tried this very smart software from my location near Hannover/North Germany now also with ADS-B, mostly with my RSP2.

ADS-B stands for “Automatic Dependant Surveillance – Broadcast” and is an automatic service where aircraft continuously transmits several vital data on around 1.090MHz. Most important part of these data is the 2D location of the aircraft which it gets by GPS plus height by a baromatric altimeter. From this position data, many other data are derived, e.g. climbing/sinking or speed. If matched to databases, you will also see type of aircraft, flight number and many other data.

“The internet” provides many services showing the results of ADS-B and other data, collected from receivers all over the world, among them Flightradar24, OpenSky, FlightAware and AirNavRadarbox. They each provide many additional data, somtimes available at different schemes. Most provide free access to much of their data, with some more specific data behind their paywall. OpenSky as a scientific and non-profit organization offers billions of datasets for free, see Scientific Datasets. QIRX uses an OpenSky data base with about 650’000 entries.

Backbone of all these services is a net of ADS-B receivers, connected via the internet and curated by each company.

QIRX shows some capabilities of such a receiving station, using a proper antenna and a simple SDR. It decodes the I/Q stream of it. ADS-B is transmitted via pulse-position modulation, or ppm. The system is explained in ICAO Annex 10 Volume IV [free download].

With QIRX, you must set the sampling rate of you SDR to 200000[Hz], as other sampling rates won’t work, see screenshot below.

To decode ADS-B, you must set the sample rate for your SDR to 2000000Hz.

After that, and having started QIRX in ADS-B mode, decoding is done automatically. Release your seatbelts, and simply relax by viewing the activities above your head. Coverage largely depends on the “view” of you antenna and a few other factors like te sensitivity of your SDR and the attenuation of your cable connecting your antenna with your SDR. Some web services, thanks to anticipatory obedience/security reasons/data protection etc., do mute some “special” flights . This is not the case, of course, with this setup. QIRX always provides stable decoding at even low SNRs – great!

Last, but not least, please find below a comparison of FlightRadar24 and QIRX setup with Flight Number TK1554/THY6KG, Hannover->Istanbul, starting from Hannover Airport. One difference between both screenshots is that at my location (Burgdorf), I got the Airbus only after it had climbed to an atlitude of 200m or so, whereas the FR24 receivers are placed at positions allowing for tracking the aircraft from even the runway.

Starting from Hannover to Istanbul: the airbus on track around Hannover. Top window shows the flight via FlightRadar24 web service, and even from the runway. Bottom window shows it received with QIRX from Burgdorf (red point in the northeast).

Also small aircraft is equipped with transponders, but not necessarily with ADS-B transponders, broadcasting the position, derived from their GPS. These small aircraft may haveonly Mode-S transponders on board, transmitting identification, height and squawk (transponder code) as assigned by their responsible ATC, or Air Traffic Control.

HF: Doppler, Signal Level and Time

Two views of the carrier of Sofia-Kostinbrod on 9400kHz from 15:30 to 18:30 UTC: On top the frequency within a window of 2Hz height only, at the bottom the synchronized HF level of this carrier; see text. [Click onto the picture for a better view.]

What you see in the picture at the top, is a mostly hidden gem of HF propagation. I took the carrier of Sofia-Kostinbrod transmitter form Bulgaria (250kW) on 9400kHz and observed it for three hours. In the upper window you see the frequency wihtin a window of 2Hz height only. You see two strong carriers: one nearly in parallel to the x-axis, the other snaking some fraction of one Hertz below it.

With one transmitter only on this frequency: How does this happen?

It’s multipath propagation. The signal takes one way via a groundwave-like way, the upper trace. It reveals a very slight drift downwards. As I use a GNSS-controlled receiver, the FDM-S3 from Elad, this miniscule drift should be happen within the transmitter, not the receiver.
The snaking trace stems from a second way, most likely via the F2 layer of the ionosphere. As the ionosphere is prone to winds and an ever dynamic change of its ionization, it is moving. And with all moving objects, also this causes a Doppler effect to waves. This is exactly what we see – the angular speed of the ionosphere, relative to the “groundwave-like” signal.
You may also see at least two weaker traces, caused by two further ways, hence showing other Doppler shift.

In the diagram at the bottom, you see the combined level of all traces. Because they reach the reeiver at different time and, hence, different phases, their addition leads to an ever changing signal level, called: fading.

I hope to continue this work with some other examples in the future, also taking fade-in and fade-out into account.

Doppler: Following Airplanes’ tracks

Carrier and Doppler trace (left), locations of transmitter, receiver and track of flight NH8406 – March 27, 2021, around 16:45 UTC [click onto the screenshot for richer detail]

Working on a project which will focus on Doppler spread of HF channels (see at the bottom) and other impairements, I also bumped into some more prominent Doppler catches, namely on the VHF aero band. I took the AM carrier of nearby Hannover VOLMET on 127.4 MHz and observed doppler traces about plus/minus 200Hz the carrier frequency. Following the acitvity in the airspace via Flightradar24 in parallel, it is easy to match traces and aircrafts. In this case, I nailed cargo flight NH8406 from Frankfurt to Narita/Tokyo. It is important to remember what is shown in left part of the screenshot: it is the signal of Hannover VOLMET, reflected by this moving Boeing 777-F. Thus, the reflected frequency shows a Doppler frequency shift – depending on the relative speed in respect to transmitter and receiver. A positive Doppler frequency signals that the aircraft is approaching my location. When it turns to the lower frequencies, I see the aircraft passing.

Things get more complex wen it comes to the Doppler shift at HF propagation. You will also see planes, but effects from high winds in the upper atmosphere, coming and fading of ionospheric layers and the influences of the geomagnetic field are prevailing. Due to the much lower frequencies, the effects are just about a tenth compared to thie above example on VHF.

See below a result from my observations on HF as a preview.

Carrier of TRT Emirler, Turkey, in the 19 meter band. Just after sunrise, the carrier splits into two, and you also see double lines due to magnetoionic effects. The window shos about 3Hz in the vertical, and about 40 minutes in the horizontal scale.

Medium Wave: Signals May tell sunris/Sunset at their transmitter’s site

The two stronger carriers (Romania left, Algeria right) exhibit Doppler-shifted scatter; see text for a more detailed explanation.

During my expeditions into the thicket of mediumwave offsets, I bumped into pictures like that at the top. In the lower part of the screenshot, you see two carriers mit seahorse-like structures looking to the right. In the evening, they look towards the West.

This is one of the several effects which can be seen at local sunrise/sunset. Here, the carrier gets “clouded” and show frequency changes. These effects are associated with Doppler shift (moving of ionospheric patches/layers) as well as scattering caused by irregularities of the ionosphere, most notably Travelling Ionospheric Disturbances, or TID. Whereas the Doppler shift, by vertical moving of reflecting layers like combining of F1- and F2-layer to one and lower F-layer when approaching darkness, is comparatively small, high wind speeds in these regions can cause a much faster horizontal movement of such regions. This, in turn, may cause a Doppler shift of about 1Hz or even higher in the medium wave range.

The Figure at the top demonstrates this effect at two transmitters on 1422kHz, namely SRR Radio România Actualități from Râmnicu Vâlcea/Olănești (sunrise 05:55 UTC/sunset 15:12 UTC; distance 1433km) and Radio Coran/Radio UFC/Radio Culture/Chaîne 3 from Ouled Fayet/Algeria (sunrise 06:58 UTC/sunset 17:00 UTC; distance 1840 km). Seen from midnight, sunrise first occurs at the Romanian transmitter, followed by the Algerian one with the seahorse-like pattern of the scatter towards the higher frequencies. Around each local sunset, first Romania sees darkness, followed by Algeria. Here, the scatter pattern turns towards the lower frequencies. In the insert at the right, contrast has been sharpened to additionally reveal a split-up of these carriers due to propagation into two paths.

This effect often helps to determine the local sunrise/sunset of a carrier. I marked what presumably is the carrier of MBC Radio 1 from Matiya/Malawi, sunrise 03:22 UTC; listed 02:00 to 22:00 UTC, but obviously on a 24 hours’ service this Tuesday.

Both Figures at the bottom try for some detective work without knowing specific offsets (because not available) but relying only on schedule and the above mentioned propagational effect. Crime scene takes place on 1233kHz, where we want to scrutinize two channels, one on 1232,9937 kHz, the other on 1232,9951kHz.

Distinctive scatter, associated with local sunrise at the transmitter, provides a strong hint towards the location.

The s/off- and the s/on pattern match that of Chinese National Radio #17’s Kazakh service. Incidentally, sunrise takes place in Qinghe at 01:42 UTC, and in Boertala at 02:04UTC – next Figure. Boertala is listed with 10kW (stronger signal), Qinghe with 1kW. Unfortunately, the f/out time of other CNR17 transmitters on this channel is mostly covered by phase noise from Rádio Dechovka in the Czech Republic and Absolute Radio in the United Kingdom.

Some CNR17 locations and the terminator during sunrise in Boertala, see text. Visualized with free Simon’s World Map.

Here I am indebted to Jens Mielich, Head of the ionosonde at Juliusruh/Germany, who was so kind to comment on this observation. According to him, the observed Doppler shift of 1Hz on 1422kHz should have been caused by a refracting medium, moving at an (angular) speed of roughly 105m/s. At Juliusruh, he observed e.g., an ionospheric drift of 311m/s±93m/s from East towards West on January 19, 2021 at 04:19 UTC: “You will get a positive Doppler shift during a West/North drift, and a negative one at East/South drift.” He adds that further investigations on a more longer time series are needed.


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