Immer noch finden Richard Godfrey & Co. unter der Yellow Press enormen Zuspruch für ihre Schmonzette, nach der sie meinen, die Route von Flugzeugen (speziell Todesflug MH370) durch WSPR-Logdaten über tausende von Kilometern nachweisen zu können.
Allerdings haben sie sich offensichtlich bislang geweigert, ihre Luftschlösser in anerkannten Fachmedien zu veröffentlichen, wo diese von einem Fachpublikum entweder schon im Manuskript (peer review) oder nach Publikation begutachtet, nachvollzogen und diskutiert werden können. Sie hingegen bevorzugen die Laienpresse, deren Journalisten aus Faulheit und/oder Unkenntnis nur zu oft treudoof einseitig das wiedergeben, was Godfrey & Co. so zusammenphantasieren.
Auch wenn etwa der Entwickler von WSPR, Nobelpreisträger Prof. Joe Taylor (K1JT), diese Luftschlösser in das Reich des Unsinns von “Leuten, die nicht wissen, was sie tun“ verbannte und Prof. Bruce Ward, Mitentwickler des autralischen HF-Radars JORN, das ebenfalls im Reich des blühenden Blödsinns veortete, halten Godfrey & Co. wacker an ihren unwissenschaftlichen Tagträumen fest.
Start einer fachlichen Diskussion
Um eine ernsthaft-fachliche Diskussion außerhalb des oft selbst-referentiellen Internet anzustoßen, habe ich in zwei funktechnischen Fachzeitschriften dieses Thema mit den Augen eines Praktikers betrachtet, ohne dabei jedoch den theoretischen Hintergrund aus den Augen zu verlieren:
“Flugzeug-Scatter auf Kurzwelle”, FUNKAMATEUR 5/2022, S. 368-372 (Aufl. 32.600) und
“Flugzeugscatter: Was geht? Und was geht nicht?” FUNKTELEGRAMM, 6/22, S.
Das Manuskript des ersten Artikels hatte ich auch der CQ DL des DARC zur Publikation angeboten. Erfolglos, natürlich.
DARC: Wie Diskussionen verhindert werden
Wie man zudem hört, soll der Vorsitzende des DARC, Christian Entsfellner, DL3MBG, bei einem meiner Arbeitgeber gegen die Veröffentlichung im “Funkamateur“ interveniert haben. Auf Anfrage mochten freilich weder er, noch der DARC-Vorstand das kommentieren und schon gar nicht dementieren. Diese einer Nötigung gleichkämenden Intervention reihte sich mühelos in die mal erfolgreichen, mal weniger erfolgreichen Versuche von Vereinsfunkern ein, Funkamateure zu bedrohen, zu nötigen, zu mobben und zu diskriminieren. [Zuletzt betroffen davon: Arthur Konze, DL2ART, den man bei Behörden denunziert hatte, nachdem er sich in seinem interessanten You-Tube-Kanal “Funkwelle” kompetent mit der Entwicklung der Funkamateure, der Vereinsamateure und den Ursachen für den Verfall vor allem letzterer beschäftigte.] Dass sich hingegen wiederum der Arbeitgeber von Christian Entsfellner, die renommierteRosenberger-Gruppe, zumindest innerhalb ihres Unternehmens ausdrücklich gegen Mobbing und Diskriminierung wendet, ist für ihren leitenden Mitarbeiter Entsfellner offenbar kein Grund, seinen DARC auf ebendiesen Sozial- und Ethik-Mindeststandard (SA8000) für den Umgang miteinander zu verpflichten.
Und dass Entsfellner etwa auf eine denunziatorische Mail von Godfrey überhaupt eingeht (schon dies durchaus eine Charakterfrage und eine Frage der Ethik dazu) sowie – wider alle Physik und Vernunft – hurtig dessen Scharlatanerien zum Gespött von Experten mit großer Fanfare weiterverbreitet, ist eine Schande für den Amateurfunk als technisch-wissenschaftliches Hobby.
Repressionen statt Diskussionen!
Ebenso seine diskriminierende Strategie des Mobbings, mit der er Diskussionen verhindert. Was er selbst ganz&gar treuherzig-zynisch bei einem virtuellen Mitgliedertreffen zugegeben hatte: “Wir” seien der “Elefant im Raum”, also ein offensichtliches Problem, das niemand anzusprechen wage. Und warum nicht? Auch das weiß Entsfellner aus augenscheinlich eigenem Tun ganz genau: “Aus persönlicher Angst vor Nachteilen und Repressionen.” Ob daraus für ihn oder die bei diesen Worten ihres Vorsitzenden ebenso treu wie stumm dabeisitzenden Mitvorständler möglicherweise etwas folgt, eine seit 30 Jahren vielfach angeregte Verhaltensänderung, etwa? Etwa ein beherztes: “Wer im DARC mobbt und diskriminiert, der fliegt!“, gar?
Nee, natürlich nüscht. Soll ja so bleiben.
Der Ast, auf dem der Elefant sitzt … Bebildert hatte Entsfellner diesen “Elefanten im Raum” und seine umständlich-pomadige Erklärung dieser Metapher aus jedem beliebigen Manager-Bullshit-Bingo übrigens mit einem Cartoon, der die Rückenansicht eines einsam auf einem dünnen Ast sitzenden Elefanten zeigt, der in eine menschenleere Savanne blickt (genau, wie auf dieser Peter Gaymann-Zeichnung der frühen 1980er-Jahre). “Voller Innenraum” in der Metapher = “menschenleere Savanne” im Bild – weißte nun Bescheid, wie der DARC tickt? Immerhin das mit dem dünnen Ast, auf dem der Elefant sitzt, lässt sich noch metaphorisch deuten – wie die menschenleere Savanne, in die er blickt. Die bei Lumas liegenden Bildrechte zur Verwendung des Cartoons ließ er den Verein augenscheinlich einiges kosten. Wenn.
Durchaus passend zu dieser Haltung mehren sich leider die Hinweise, dass der “Entwurf der Strategie ’75 plus 100′ für DARC e.V.”, den ich noch vor Tagen für eine “brunzdumme Fälschung”hielt, möglicherweise doch echt sei. Inklusive Lob des SA-Mann als Märtyrer und Ansichten über freiheitlich-demokratische Regierungsformen, angesichts derer ich nur schwer zwischen “noch AfD oder doch schon Reichsbürger?” zu entscheiden vermochte. Auch hierzu natürlich nix Offizielles vom DARC. Ich hoffe doch sehr, dieser Sache bei Gelegenheit näher auf den Grund zu gehen.
I was asked to give a short overview of how to calculate the received power, scattered by an aircraft on HF. The answer is easy if we focus on AM DX signals from broadcasting stations, illuminating an aircraft. In this case the spectrogram, Figure 1, shows the carrier as well as the scattered signal – the latter being the Doppler trace. We also can easily measure both signal strength and calculate their difference. This has been done for the maximum values of carrier and Doppler in Figure 2 below:
Mean value of the carrier in the analyzed 10-minute’s part of the whole observation is -32.7dBm at a standard deviation of 4.98 – see Figure 3 below.
Backbone of all calculations is the well-established Radar Equation. Let’s think of it as a reliable, but Black Box. Critical points are in this case:
distance aircraft -> receiver
reflectivity of the aircraft at the specific frequency (radar cross section, or RCS)
I took a strong broadcaster, namely Kashi, running 500kW AM (250kW carrier) on 17’650kHz on a curtain array antenna with a gain of ca. 20dB towards Central Europe. Effective Radiated Power (ERP) of the carrier is 104dBm. An approximate calculation (free-space loss, the prevailing attenuating factor with propagation) over this distance of 5’109km and at 17’650kHz via Matlab’s fspl function yields an attenuation of 131.5dB, resulting in a signal of -27.5dBm. As 2-hop ionospheric HF propagation is not exactly free-space propagation,so a VOAAREA HF propagation simulation had been done, giving the transmitter’s footprint in dBW (add 30dB to get dBm):
The illuminating power, a proxy for transmitter power within the -65dBW footprint in Figure 4, measures -32dBm. The minimum slant distance between the aircraft and my location measures 1000m. The RCS of this aircraft is given at 10 … 100, let’s generously take 100, because the wingspan of the given aircraft (35m) almost exactly measures 2*wavelength (17m) in this case providing strong forward and backward scatter.
What value can be caclulated from as scattered signal which me measured -63dBm at highest? According to the equation #6 given in OTH-B Radar System: System Summary of the University of Massachusetts Lowell, we land at a level of -62.1dBm, given the mean value of the carrier with -32.7dBm. This almost exactly matches the measured value of -63dBm.
Now some people claim to “see” and even identify aircraft not over a few tens of kilometers, but over many thousands of kilometers. Let’s check this. Figure 5 shows the development of reception levels over distance, sticking to the Kashi example as above. You see the signal peaking to slightly above -20dBm at about 1’800km distance from the transmitter. And you see the separation from one-hop to two-hop propagation at a distance of 3’000km from the transmitter.
Please keep in mind that this is only a rough calculation, not taking into account several factors, among them:
fading of the carrier (see Figure 3)
pearlstring effect of the Doppler
change of effective RCS due to different horizontal and vertical illuminations angles
That’s a powerhouse – but what about WSPR?
In praxi, I observed Doppler traces only from aircrafts at a distance not more than a very few ten kilometres from my location – given that they are illuminated by a multi-hop DX signal from a strong broadcaster.
In contrast, some people claim to have not only observed, but even identified aircraft
over thousands of kilometres,
illuminated by a 5W transmitter
Let’s take a look on this, same conditions as with the Kashi case above. First, we do the VOAAREA simulation. I took extraordinary benevolent conditions, taking a 50W transmitter (WSPR mainly runs between 1 and 10W) at an isotrope antenna of 10dBi gain. The system loss mounts to about -50dB over the Kashi case. The VOAAREA simulation (Figure 6 below) largely reflects this situation, delivering a signal of about -115dBW/Hz [WSPR] over -65dBW/Hz [Radio China International].
How far will the scattered signals reach?
Now for the crucial question: How far will scattering from both signals (-65dBW from the broadcaster, -115dBW from WSPR) reach? You will find an answer in Figure 7, below:
From Figure 7 we see scatter from the strong broadcaster sinking into the noise from a distance aircraft-receiver of 200km. WSPR from DX is good only for distances up to 10km.
This calculation has been done under unusually generous conditions, among them:
RCS has been set to 100, where 10 … 50 would be the regular case, resulting in a much reduced performance
forward/backward scatter have been applied to the calculation as well as to the measurements. This seems justified where the aircraft heading was 295° and Kashi->DK8OK was 302°, resulting in backward scatter from the wings and, thus, the strongest signal
the wings of this Airbus A320 do perform like a dipole of two wavelengths
only the strongest signals have been taken into account
neither fading of the illuminating station, nor the pearlstring-effect of the aircraft – due to phase changes under moving – have been taken into account
In praxi, such a strong DX signal never showed Doppler traces at distances of more than, say, 60km. I owe this observation also to the physicist Dr. Victor Iannello, who kindly examined many of my spectrograms with a Python program written specifically for this purpose and determined the distances of even the faintest Doppler traces, as seen at .1Hz bandwidth (+10dB system gain).
Caveat: Please keep in mind that this case is valid only for DX (i.e., multi-hop) signals illuminating the aircraft. If aircraft is illuminated by a transmitter’s backscatter signal (at a distance of ca. 100 – 1’000km from the receiver), other mechanisms take place resulting in Doppler traces from aircraft at an height, which “sees” both transmitter and receiver – see for “radio horizon”. This speical case is not covered here, and plays no role either in the texts of the WSPR/MH370 proponents.
PropLab is the Gold Standard in available raytracing software for propagation analysis on HF. To its already unique features, like 3D-raytracing revealing x- and o-rays, an updated version added a “Backscatter” option. This even more mimics reality.
From most of their literature, radio amateurs know that there is a “Dead Zone” surroundig a transmitter, where no signal is said to be available from antennas radiating their electro-magnetic field with a low elevation angle for DX. However, a steeper angle for NIVS overcomes this. But from our practice we know that this “Dead Zone” isn’t flat dead but is filled with (weak) signals.
Those can be observed at best with strong broadcasting station some 50 to 1000km near to you, but pointing to region far away. In Central Europe, transmitters in Issoudun (France) and Nauen (west of Berlin/Germany) are great candidates for such effect, called backscatter.
Cary Oler, author of PropLab, now literally fills this gap, ans shown in the tow screenshots at top of this page.
Where’s the beef? OK, among radio amateurs, backscatter is not the preferred method of establishing contacts. The professionals, however, enjoy a relatively stable signal via backscatter. And for us radio amateurs and SWLs, it gives an explanation for some weird propagation, e.g., the near-enhancement of scattered signals by aircaft scatter – see screenshot at the bottom of the page.
Thanks, Cary, for continously improving PropLab!
P.S. (12MAR2022) Today, Cary released version 31 which many improvements don’t reflect the small change of version numbers from just 28. He wrote:
There were some changes / improvements made to the signal strength calculations. We are using some improved absorption calculations. The latest update (22.214.171.124) also includes some additional revisions, including the display of signal power in ray-tracings and broadcast coverage maps in dBm that may be more handy for people who work in dBm. A researcher at MIT also caught a bug in our backscatter engine that we have now corrected in the new version. Bugs were also squashed in the broadcast coverage maps. The broadcast coverage section now also supports large ray-tracing datasets much better than prior versions. The software doesn’t choke like it used to on large datasets of even a million ray-tracings or more. With prior versions, the software looked like it was hanging, it took so long. We also added a simple theoretical noise floor calculator in the antenna tab. And we have revised the manual again to discuss some of the new functionality and improve clarity on the backscatter features. All in all, this is a fairly substantial update given that we only bumped the version number from build 28 to 31.
It seems to be a never ending story: again Richard Godfrey and Dr. Robert Westphal, DJ4FF, go on a fool’s errand regarding “WSPR and MH370”. Against all physics and reason, they continue to try to prove that it is possible to detect aircraft – and now: missiles – based on the log data of weak WSPR signals documented every 110 seconds. Even WSPR developer and Nobel laureate Joe Taylor, K1JT, has relegated this to the realm of unscientific folly: “Anyone who does this doesn’t know what they’re doing.”
Although in the aviation press and also among HF experts the support of these charlanteries is rapidly dwindling, the duo nevertheless succeeds in promoting them successfully and with great fanfare, especially among radio amateurs and their media – “because they don’t know what they’re doing” (both parties). There a scientific discussion is suppressed so far, on the contrary: One feels reminded of the flickering will-o’-the-wisp in the windows of burning asylums.
The duo’s latest folly is titled “SpaceX Falcon Launch and WSPRnet Detection,” to be precise: not doing that. In this, they stir together ignorance of HF propagation and apparent lack of expertise of what WSPR can and cannot do into an unpalatable mush. Again, it is a matter of inferring aircraft from data in the WSPR log when the signal-to-noise ratio in the logs behaves “unusually”.
With another new approach, I would like to show that what is ordinary about HF propagation is precisely its unusual nature. For this, I studied the carrier of the Riyadh radio station on 15380kHz (two hops) over four consecutive days for two hours each. The transmitter radiates with 500kW transmit power at a HRS4/4/.5 with about 20dB gain towards 310° and is thus able to provide also for some aircraft scatter detectable by Doppler traces.
The first question is: How do the signals develop, day by day? The figure below shows the levels on the four days with a resolution of one second.
The second question is: Is there any correlation of the levels? The figure below clearly says: Nope.
But the WSPR log saves only the average SNRs in chunks of 110 seconds each. So, the third question is: How do those chunks develop day by day? The figure below gives an overview:
This also calls for a correlation matrix:
The fourth question gets us right to the core: Can we see from the SNR data, by their “unusual change” some aircraft scatter? To scrutinize this question, I calculated the level difference of one chunk to the next. The idea behind it: If aircraft scatter is detected, there will be an “unusual” change of the level, most probably to a higher one. See below for this figure:
Now let’s check the spectrogram of the HF recording to see where there are some real aircraft scatter, and if they correlate with the peaks of above figure. Here, I did this only for the first day because the result is similar on all days:
So, “nothing heard”, as they say in DXpeditions … Let’s try it vice versa: we not the biggest peak around 08:28UTC. According to Godfrey and consorts this should be “unusual”, and hint towards an aircraft! But see the spectrum below: Nope!
I am convinced that these easy-to-understand, yet scientific accounts of the actual propagation conditions should convince even the simplest mind: The detection of aircraft etc. with WSPR log data is not possible.
Last but not least, the figure below shows how little aircraft scatter affects the carrier signal. Moreover, most of the Doppler signal is outside the 6 Hz bandwidth of a WSPR signal. And for fun, everyone can calculate that the Doppler signal is at least 40 dB below the carrier signal. If the carrier signal is -50 dBm and the Doppler signal -90 dBm, the latter would be raised by 0.0004 dBm. If, yes, if this Doppler trace fell directly on the carrier …
Surely some proponents of the thesis that nevertheless airplanes are detectable at great distances from WSPR log data (admittedly only on an earth as a disk, which they may believe in …) will not be further disturbed by the physics presented here. What again does not disturb me. As a disgrace for the amateur radio, however, I feel, if these people bring their crazy mumbo-jumbo, as usual, with denunciatory mails to institutions of the amateur radio and these – obviously from low motives – also still give place to it. This makes amateur radio look technically dumber than the majority of radio amateurs actually are.
Since scientific discussion on the website “The Search for MH370” under the half-megalomaniac subtitle “Serving the MH370 Global Community” is suppressed by its operator Richard Godfrey, a pensioner from Hesse, my blog is explicitly offered for corresponding discussions and rebuttals. It may be easier to successfully suppress facts in this matter with denunciatory e-mails to the DARC chairman – to write such mails is as much a question of character as to follow them at all – but nevertheless it can be exciting to learn something more about “alternative physics”.
Here is my comment suppressed on Godfrey’s website:
Hi – the new paper by Westphal et al. attempts to demonstrate a rocket start from WSPR log data. However, it is not clear from the paper in which way this proof should have succeeded. Apparently, “SNR anomalies” of the HF propagation are used for this purpose without distinguishing the term “anomalies” from the “normal case”. It would be interesting if the authors could explain exactly this in a comprehensible way. I am also asked for the long announced paper, in which the authors wanted to dedicate themselves to HF propagation and aircraft scatter and in which hopefully also representations/calculations of the radar cross section find entrance. There is a lot of preliminary work on this that meets scientific standards – and the community is now eagerly awaiting a methodology that will make this surprisingly possible for WSPR log data as well. How strong the dynamics of the ionosphere are, and that Aircraft Scatter is clearly not detectable in the sum signal, but only by FFT analysis, I have presented in my latest blog entry: https://dk8ok.org/2022/02/14/wspr-and-mh370-revisited-some-notes-on-fading/ 73 Nils, DK8OK
Furthermore, there are people who claim against all facts and reason that they can prove aircraft movements with aircraft scattering of WSPR signals from their log data. Surprisingly or not, they find enthusiastic approval in the popular press, but also in technical-scientific organizations like many ham radio associations, first and foremost the notorious German DARC. Whether one deals with supporters of “conspiracy theories” at all (Nobel laureate Joe Taylor, K1JT, said having too little time for such obvious and non-scienctific nonsense), or whether one meets their convoluted theories with technical-scientific arguments, is quite controversial and a topic more of social psychology than one of physics.
Nevertheless, “Never Give a Sucker an Even Break” as the great comedian and juggler, W.C. Fields stated 1941. And that is why I would like to deal with some “arguments”, which would not be difficult because of the subject matter, but because of how these people “argue”. For the sake of clarity and brevity, let’s do this in the form of a question and answer game.
Do aircraft affect RF signals? Certainly. HF signals are scattered on the electrically conductive metallic hull of aircraft.
How does Aircraft Scatter work at all? The drawing at the top explains it: Radio waves from a transmitter reach the receiver directly on the one hand, and via aicraft scatter on the other. On the receiver side, both signals add up. Thanks to the Doppler effect, which the signal part scattered by the aircraft has, both signals can be separated from each other again with a method called FFT; see my website for a couple of examples. However, this is not possible with WSPR log data, here only the total signal is noted.
How big are these influences? They mainly affect the signal strength and are around 35 to 50dB+ below the original signal. There are exceptions. Downward, there are far more cases than the exceedingly rare constellations where the scattered signal may be larger than the original signal. Above 30 MHz this occurs more often, below 30 MHz I have never observed it as there always was at least some backscatter of the original signal. Signals or field strength can be measured and calculated. Generally speaking, a suitable form of the “Radar Equation” will do the calculation, see here. They largely match the values being measured by the method “separate original signal and scattered signal”.
Facts, please – how big … ? Sorry, yes. Say, a booming signal by a broadcaster in the 19 meter band hits your antenna with a level of -40 dBm. Then a Boeing 747, flying over your house to touch down at your airport nearby (“in your backyard”, as they say) at a distance of 500m only, this will peak at -86dBm. Not bad, and easily visible by FFT analysis.
How much does this scattered signal adds to the original signal? Good, with this you steer to the central point, because WSPR measures only this total signal. You just have to add -40dBm and -86dBm and with this most favorable constellation you get a total signal of -39.999890911528446dBm. Believe me: you cannot distinguish it from the level of the original signal, being -40dBm.
Oh, that’s disappointing … but they tell they can identfy aircraft not only 500m, but some/many 1000km away? First, physiscs may be disappointing. Secondly, I took a most favourable case – booming broadcaster, short distance. The effective power of a stronger WSPR transmitter may reach 40dBm, compared to 100dBm+ of many broadcasters. The difference of 60dBm and more is whopping.
“Whopping” – what do you exactly mean by this? Take the example of the broadcaster, reading -40dBm on my S-Meter. If the transmitter were an even above-average WSPR transmitter it reading of the S-Meter would be -100dBm. Still readable, and WSPR would give a decode.
So, it works? Wait a moment, for introducing the scattered signal, also 60dB down. It will peak at -160dBm, and it reliably is eaten by noise which will start between -130 and -140dBm. By this, the orginal signal of -100dBm will be enhanced and strengthed to -99.999995657057354dBm. Quite an achievement!
I understand, it cannot work. Does a greater distance improve things?! By no means. A greater distance worsens things even exponentially.
OK, but what the hell are they measuring to come up with such far-reaching results? They are measuring indeed fluctuations of the signal but without knowing the reason. And there are much more and of stronger influence to the received signal level than aircraft scatter. Prevailing is multi-path leading to near-normally distributed changes of the signal level of around ±8dB from second to second, and often more than 30dB within just a few seconds!
But – they mention “drift” … and “Doppler” means “drift”?! Yes, but the “moon shapes” of a few signals surely have other reasons, much more obvious – just think of bad power supplies, meteor scatter (stronger and more often seen compared to aircraft scatter) and travelling waves within the ionosphere itself. Have you ever asked yourself, why in the presented cases the whole signal is shifted, instead of seeing a Doppler signal branching out from the original signal? „They don‘t know what they do“, says K1JT into their direction.
How much can I rely on the quality of WSPR signals? Look yourself at the screenshot below, showing three hours of WSPR signals, showing drift, over-modulation, noisy signals. All fine for decoding WSPR but on only very few you consider those rocks where you want to build your church on (Mathew 16-18). You see instabilities at many scales, and also the duly repeating (!) half-moon footprints which for some ghostseers are the evidence of aircraft.
They work with the concept of “tripwire”. Any comment on this? Well, they seem to consider propagation working by distinctive, laser-like “rays”, not fields of energy. (This is just a guess from this blog entry.) Each object crossing this ray causes a-normal propagation which they fail to precisely specify. This is a fundamental misconcept of how HF propagation works plus an incomprehensable application of PropLab Pro 3.1, the propagation software, which they seem not to understand. Propagation doesn’t produce “tripwires”. And if you need some parallel, you should more think of a booby trap, thanks to which not only signals are pulverized, but with them all the dream fantasies that this or that plane may have caused them to go off. They must use “Broadcast Coverage Map” with PropLab Pro to get a realistic view of electromagnetic fields and their propagation, see secreenshot below.
Can I understand your assertions? Absolutely! In theory, as well as in practice. You can find many examples on my website. A SDR and software are all you need. Oh, and, last but not least: and unbiased view not on the possibly desirable, but on the physically possible!
But why do they still spread their charlanteries with great success? Look around you. The world is full of castles in the air. That’s actually not so bad. Here, however, they are built by those who could know better and they are spread with enthusiasm by those who know better. Or at least should know better. But that is the usual pattern of Fake News. Only that it undermines the technical-scientific competence of the radio amateurs and makes them look ridiculous.
Simon Brown, G4ELI, author of free SDRC software to control (and much more …) most of the SDRs walking on earth, again surprised the community: he added a stunning fast “Bitmap Display” to get a literally overlook onto the content of a recording. The screenshot at the top shows a 25 MHz recording over 24 hours, made with Winradio’s Sigma SDR (16 bit), produced from a near-9TB file within only few seconds. It clearly shows how propagation follows the sun. Medium wave signals thin out after sunrise (06:56UTC here on 23NOV2021) to fade in just before sunset (15:16UTC). You also see the still active broadcasting bands, and, alas, also some interference from PVs at the higher end of the spectrum. You also see the power of s state-of-the-art SDR like this Winradio Sigma, at a professional wide-band active vertical dipole antenne MD-300DX.
See, for comparison, the range of 24MHz/24 hours on a summer day, namely 08JUN2021 (SR 04:00/SS 19:39 UTC), with Elad FDM-S3:
This “Bitmap Display” is called via the tab “Rec/Playback“, then menu “Navigator“. It works on recorded HF files with a fixed width of 4096 data points. So, with a recording of 25MHz width you get a freqeuncy resolution of roughly 6kHz. This makes it ideal for AM broadcast under 30MHz, as well as for all wider modes above 30MHz, let it be the full FM band to identify even short openings, the airbands to check most active channels etc. The time resolution can be set between on second and 60 seconds, see screenshot below.
This “Bitmap Display” adds to the alread known “Grid Display” which still is on board, see the two screenshots below.
Both displays set the recording to the matching time by just a mouseclick. The frequency, however, has to be set separately in the “Receive” Panel. You can switch beween this two windows with a tab at the left bottom, see the following two screenshots.
The ingenious double function “Click and display time and frequency” is still reserved for the File Analyser module, which is somewhat more complex to operate.
More than just a consolation for this, however, is the loop function: here you set the times for the start and end of the loop by numerical input or simply by mouse click – and off you go! See the both screenshots below:
One very fine feature is zooming into the “Bitmap Display”. Even though this software zoom does not change the resolution, this function is an important tool for checking the occupancy of a broadcast band, for example, and for jumping specifically to the start of a broadcast. Frequency-wise – by position and bandwidth – the slider below the running Spectrogram (“Waterfall”) of the main window is responsible for this. This can be moved as well as changed in its width, so that the corresponding area is displayed. The following two screenshots are more helpful than any quick guide.
It is also possible to tune to a specific frequency when only the “Playback” window is open, and not the “Receive” window. This workaround-like procedure is done by the function/window “Frequency Database” which has to be filled with at least one set of channels. I use the voluminous ILG for this. With this or another database already loaded, click View -> Frequency Database. Your SDRC window should look like the screenshot below:
Then set all the demodulation controls to match the type of signal you want to recevie, i.e., AM and 5kHz etc. for broadcast. In the next step, simply double-click to the frequency entry in your “Frequency Database”. The “Receive” frequency changes (as you might hear). If your displays had been zoomed and the new frequency is out of focus, a simple trick brings the new channel to full glory: click to “Centre”, see screenshot below.
Thanks, Simon, for another great feature of your software!
What are the main differences between the “Bitmap Display” and the “File Analyser”? * The “Bitmap Display” is by far faster to build up a spectrogram. It also features the whole bandwidth of a recording. * The “File Analyser” is more flexible in frequency resolution, offers “see, click, tune” when a spectrogram has been built up, and features flexible CSV export of data – up to the whole spectrogram. But it takes much looonger to build up.
Can the “Bitmap Display” also being used to raise short-living utility signals like ALE? * It depends. Limiting factor is the frequency resolution. With some experience, I can clearly make out ALE signals in an 1MHz wide recording, 1 second time resolution.
Do you have a wishlist? Thanks for asking, but it is an only small one: * It would be nice if there were several options for (higher) frequency resolution. OK, it will slow down processing, but … * As I like to process spectrograms, a CSV export would be welcome (as with the File Analyser). * Undoubtedly, to change not only time, but also frequency would be the ice on the cake.
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.
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):
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:
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.
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:
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:
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:
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.
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.
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 upto 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 SDRCwith 0.39 Hz resolution, see screenshot below. The latter provides the numerical output used in the following post-processing.
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.
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:
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 …
For the complete overwiew of the steps see the workflow below:
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”).
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
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]
In this second part about DAB/QIRX, I will deal with anaylzing some results of QIRX’ log.
QIRX software provides several tools and data for DAB reception which it stores in a file called TII logger. TII stands for Transmitter Identification Information. Most important of these data are:
Time of reception
Ensemble ID – identification of the DAB-VHF channel received
Signal-to-Noise ratio, or SNR, of the whole 1.536MHz wide VHF channel. Maximum values here are about 34dB from locals. Audio can be expected from about 9dB, reliable decoding of metadata from around 7dB
Main ID and Sub ID of the physical transmitter’s location
Strength – the average of the amplitudes (magnitudes) of the TII carriers of each transmitter at that moment. The strongest carrier within an ensemble gets value “1”, the other carriers a number from 0 to 1 in respect to their relative magnitude, compared to the strongest carrier. Scale is linear, not logarithmic.
For mobile use, also GPS data in 3D are stored, extracted from an NMEA stream, provided by e.g., an external GPS mouse.
There are two principal methods of collecting data:
Scanning the whole DAB-band with all ensembles or scanning a couple of ensembles, as set in the Options’ tab, see Figure 2. This is done to get an overlook over all or many ensembles.
Scanning of just one ensemble, mostly to scrutinize propagation from the physical transmitter’s locations – Figure 3.
For scanning, the position of the Threshold slider is important. This can be considered as “kind of a squelch”. It sets the threshold where an ensemble/service is logged. You can control this feature via the window “TII Carriers”. A high threshold results in reliably logging of the strongest station(s). A low threshold will save also weak(er) signals but may be prone to false positive logs which have to been checked/erased manually.
Scan the whole Band
A scan of the whole band with a high threshold (here 0.54) resulted in the ensembles of Figure 1. Reception has been done from a fixed location with a largely vertical-polarized discone antenna at a height of about 50m near Hannover, in the lowlands of Northern Germany. The radio horizon is about 30km, following the equation given by Armbrüster/Grünberger: Elektromagnetische Wellen im Hochfrequenzbereich, München/Heidelberg [Siemens], 1978, p.48. Their factor of 4.1 is a bit higher than other values also found, ranging around 3.6. Receiver is an SDRPlay RSP2.
Figure 4 shows the SNRs of three ensembles, transmitted by the local Telemax tower at 15.8km with antennas at a maximum height of about 340m above sea level, or ASL. This results in a radio horizon of 75km.
Both 10kW signals of ensemble 5C and 5D show a more or less similar SNRs, but at different medians of 27.0dB [ensemble 5C], 31.3dB [5D] and 27.1dB [7A], respectively. With (nearly) the same power and the same horizontal polarization – matching my vertical Discone antenna -, with 5D leading the pack by a whopping 4dB, or factor 2.5, presumably using another antenna pattern at the transmitters’ site. What puzzles me more is that the variance of ensemble 7A with 1.56 is more then double as high as with the other signal (0.62 and 0.70).
The next diagram (Figure 5) shows the SNR from ensemble 11C, transmitted from Brocken mountain. With a height of 1141m, it is also virtually line-of-sight. There we see a much lower SNR, due to the fivefold distance, plus the transmitter’s power of being only a fourth that of Hannover Telemax. With 10.2dB, the median SNR is barely above the reliable threshold of around 10dB to provide audio at all. Showing a variance of 0.9, it is prone to sink under this vital level – returning no audio then. The three bigger dips largely coincide with local sunrise, noon and sunset. Further studies are needed to get a clue on that.
The last diagram of this series, Figure 6, shows a splash of DX: From my location, the transmitter “Eggegebirge/Lichtenauer Kreuz” only provides marginal reception – with a median SNR of 8.6dB and a variance of 0.3 only rarely jumping over the threshold of 10dB. Sometimes, even metadata are lost, resulting in a somewhat thinned-out appearance of the diagram. If you compare the diagrams from Brocken above and from Eggegebirge below, you may see some similarity in SNR over time with also pronounced dips around sunrise, noon and sunset.
Scanning one Ensemble
In a second step, I scanned just one ensemble for 24 hours, namely 9B “NDR NDS LG” on 204.640MHz with a choice of six stations – some easy, but e.g. Stade a bit challenging. Figure 7 shows the locations and some results, from a whopping number of 276’092 logs. For this, “Threshold” had been set to the lowest possible value, combining highest sensitivity with a maximum of false hits (here: nearly 30%) to be sorted out later – which of course had been already done in this example.
To get the performance of each transmitter’s locations within one ensemble, you cannot use the SNR values, as they refer to the strongest station within the ensemble: Visselhövede in this case. Hence, I had to use column “Strength” of the TII log, running from “1” for the biggest signal in the ensemble to “0” on a linear scale. Here, the smart guys of UKW/TV Arbeitskreis e.V. have invested much work in identifying the TIIs. If you match the Main/Sub Id of your TII log with their free publications, you can assign the IDs to their locations.
This has been done for Figure 8, sorted by distances of the transmitters. The Bispingen/Egestorf (74.2km) transmitter is running only 2kW, hence its strength is weaker and more patchy than e.g. 10kW transmitter Dannenberg/Zernien, despite its distance of 91.2km. Most prominent in the diagram of this transmitter, you see two peaks between 18:00 and 00:00 UTC. They occur – each time-shifted and weaker – also in the diagrams from Egestorf, Lüneburg and Rosengarten plus, much weaker, Visselhövede. Source of these peaks almost surely is a “moving reflector”, being more an airplane than an atmospheric phenomenon, enhancing reception currently. Websites like Flightradar24 with their playback function will help to find some suspects.
Finally, an alternative look at strengths. In Figure 9, I combined the strengths of just three transmitters, now having set a logarithmic vertical scale, rather than a linear scale to emphasize the weaker signals.
Some Notes on Propagation
Last but no least, I like to add some notes on propagation. In the DAB frequency range, of around 170 to 255 MHz, propagation largely follows “line of sight”, primarily controlled by the height of transmitters’s and receiver’s antenna – plus power of the transmitter and sensitivity of the receiver. Antenna polarization also plays a role – the polarization of the receiver’s antenna must match that of the transmitter’s antenna to avoid losses by a mismatch. Bear in mind that many transmitter’s antennas may have a non-omni-directional diagram.
This general propagation can be enhanced or degraded by atmospheric phenomenons, high or low pressure/temperature; by rain and fog, by aircraft scatter and other factors.
The SNR of an ensemble is mostly as better as the signal is stronger. There is an exception: if the same ensemble is received by two transmitters at a relative distance of more than about 75km, the “Guard Interval” is too short to sort them out. Result then is a reduced SNR at a high signal level. However, I never faced this situation.
Clem dropped my attention also to another most valuable tool, provided by fmscan.org. They maintain detailed databases also on DAB transmitters, their antennas, powers, ensembles etc., and a web service which will draw circles of coverage onto a map. This is a cool and free tool, you must not miss – see Figure 10.
The above mentioned tool does not take into account topographic data which may be important to calculate the coverage in mountainous regions. Here Nautel, a Canadian producer of transmitters, provides a free webtool after registration, see Figure 11.
Digital Audio Broadcast, or: DAB, now is common with most household and car radios – after a more than bumpy start. Pressed into market with voluptuous grants from the tax payer and unabashed blackmailing of ceasing all FM broadcast and, hence, making all analogue FM radios obsolete without any financial compensation.
After fierce protests, there is some coexistence between both ways to the listener – mostly thanks of the pressure of commercial broadcasters which often belong to media giants.
Software defined radios, or: SDRs, make an excellent start to discover both worlds. Here, I will focus on DAB with free software QIRXby Clem Schmidt, DF9GI, from Frankfurt. It directly works with RTL-SDR, Airspyand RSP2 SDRs. I tried this very smart software from my location near Hannover/North Germany, mostly with my RSP2.
This blog has two parts: in this first part (1/2), I want to get some ground under my feet – regarding DAB as well as QIRX. The second part (2/2) deals with some results of QIRX’ logs.
QIRX excels in a number of analytic tools, and an OSM-based map showing your location as well as the locations of the transmitters, all metadata transmitted plus other features like connection to GPS receiver’s NMEA output for mobile use. It can be also used very basically: just to listen.
DAB – an efficient concept
In the first step, you have to find out which transmitters you receive at your location. Each transmitter beams a so-called “ensemble” (also dubbed “bouquet”) into the country, or a bundle of programms. Many of these programms or services can be packed into just one physical DAB-VHF-channel (“block”, e.g. 5D) of 1,536MHz width, via a robust and spectrum-efficient mode, called OFDM. This is a special combination of phase-modulated carriers, commerically pioneered for DAB by Munich-based Institut für Rundfunktechnik from 1981. Each ensemble carries an Ensemble ID (EId), like 11F7 for “Antenne DE”. Thanks to the “Extended Country Code”, this EId is worldwide unique. In turn, each station/programme/service within an ensemble carries an unique Service ID (SId), like 121A for “Absolut OLDIE”. Some identical ensembles may be aired from different locations/ transmitters within a service region. In this case, they work together as a presumably GPS-synchronized Single Frequency Network – to which we’ll come later.
QIRX – the easy start
QIRX offers a scanner, catching all these ensembles from all the transmitters within the reach of your antenna:
At my location, QIRX scanner offers nine to ten such ensembles. For this example, I choosed the ensemble “Mitteldeutscher Rundfunk – Sachsen-Anhalt” (MDR-S-Anhalt), and clicked on the list of eleven services to “MDR Klassik” which shows up with some data on service quality plus multimedia:
It offers perfect reception, despite of delivering a signal-to-noise ration of just 10.9dB from a transmitter at a distance of 80+ kilometers.
Scanning is done in the background, and it may loop through (click: “Scan forever”) for hours or even days. It continually writes the results in the TII Logfile for future inspection – a great tool which will reveal even short openings over a specific time – scatter by tropo, aircraft or meteors among these.
How is the signal?
As an SDR aficionado, you will be pleased to see the spectrum and the spectrogram (“waterfall”) of the signal, the receiver is tuned to. The first screenshot below shows a near-perfect case from my local transmitter in 15.8km distance, delivering an SNR of up to more then 33dB, whereas the second screenshot of the ensemble “11D/Radio fuer NRW” at a distance of 115 kilometers shows a bumpy road ahead with SNRs well under 10dB. The “radio horizon” of this specific transmitter’s site already ends at about 85km, thus the margin is not too high.
One of the most exciting features of QIRX are its analytic tools. To make full use of them, a basic understandig of the concept of DAB is inevitable. ETSI, the European Telecommunications Standards Institute, is the umbrella organisation for maintaining also this concept. They provide a widespread number of different papers with standards and technical reports of which I found EN 300 401 (focusing on receivers) and TR 101 496-3 (focusing on the operation of a DAB network) especially helpful. Clemens, the software author of QIRX, has published some excellent information on these topics on his website, where I especially recommend the two parts dealing with TII, or Transmiter Identification Information. He had put a lot of work into it to present all information to get a clue what happens behind this rather complex and smart DAB system.
The window for the analytic tools comprises up to five sub-windows, with the Audio Spectrum skipped here:
Let’s got through them step by step.
Constellation shows the four phases of the robust DQPSK modulation in a linear manner, representing each of the sub-carrier of the OFDM signal separately. By this, you may see which of the carriers actually is degraded by multipath propagation, caused e.g. by reflection from aircraft. Above, you see the constellation of a near-perfect reception with an SNR of 33dB. Below, you see two examples at a much lower SNR. At the third example, the robust meta information from the Fast Information Channel (FIC) already is decoded, with however, the signal strength (more exactly, the SNR) just under the threshold to provide audio decoding.
Channel Impulse Repsonse (CIR) shows the time of flight from all transmitters to the receiver – referenced to the strongest signal, showing up as “0”. You may switch the scale from samples to time in microseconds to (relative) kilometers. These data also show up in the TII window at left-hand, and are used to populate the map. It is the easy-to-read surface of heavy work under the hood to which also some other radio enthusiasts had contributed. Below you see first the CIR display, where you see signals from three transmitters. The X-scale is in microseconds, time-of-flight, referenced to the strongest signal. On the left you see a list of all three received transmitters, ensemble 5D, with their real distance (km abs.) from the receiver, their distance relative to the strongest signal (km rel.), and their direction as seen from the receiver (AZM) – to turn your antenna into the right direction …
TII Carriers is a unique and exciting tool of QIRX software to look a bit deeper into the structure of the Single Frequency Network to which DAB is organized. Let’s take the map above with three transmitter on the same DAB-Block, or: VHF channel. TII or Transmitter Identification Information tells us just what transmitter(s) we do receive. Clem, the author of QIRX, put a lot of work not only to get this tool running, but also in describing the background and how to use this feature – you must not miss this (there are two parts …)! I can give only a weak echo of his very well placed explanations there.
Basically, it decodes the “Null symbol” of the TII which is transmitted with low power within what seems a “pause” of only 1.3ms of duration between each frame of DAB stream, being itself 96ms long.
The most easy situation is to receive and decode only one transmitter. The following screenshot shows this situation with DAB-VHF-Block 9B, transmitter Visselhövede. In the TII window you see 4 x 4 carriers, separated within four compartments by a dashed vertical yellow line. Each of the four groups of carriers contain the same information, but each taken from a different part of the spectrum to enhance overall sensitivity for weak(er) stations. The position of the TII subcarrier defines the sub-ID, and, hence, the individual transmitter. In this case, the sub-ID is “1”, denoting Visselhövede as transmitter location. The mapping of DAB-VHF-Block, Main/Sub-ID and transmitter site has been mainly done by UKW/TV-Arbeitskreis e.V., a smart group of enthusiasts dealing with reception above 30 MHz.
If you play around with the “Threshold” detecting TII carriers this may reveal also other transmitter locations, transported via the same DAB-VHF-Block. So, I lowered the threshold to 0.010 (x10). As a result, much more TII carriers become visible in the four compartments. They belong to other sites, hence, bearing other sub-IDs. To decode them, they must show up almost similar within all four compartments of the carrier spectrum window (right). Only then they are duly listed under the TII tab on the left side, and show also up in the map at the top.
You see 4 x five carriers, jumping over the gray threshold. On the left, they all are listed with their metadata including their sub-IDs of:
1 Visselhövede – 65,8km/10kW,
2 Dannenberg/Zernien – 91.2km/10kW,
5 Bispingen – 74.2km/2kW,
6 Lüneburg/Neu-Wendhausen – 96.1km/4kW and
4 Rosengarten/Langenrehm – 106,8km/10kW
The additional four sites duly show up in the map, in red with the fifth, Visselhövede, marked green as carrying the best signal.
I/Q Data: The diagram always shows the time sequence of IQ data, in units of samples. Here, one sample corresponds to the system clock time of 1/2048000 sec, i.e. about 1/2 microsecond. The Y-axis can be switched between “Magnitude” (roughly the absolute amplitudes of I/Q), or just the amplitudes of the I-data (“I-Data” ticked). The first is the tool of choice to reveal the above mentioned “Null symbol” of 1.3 milliseconds, see screenshot below. For a detailed explanation, which is out of scope of this blog entry, please refer to QIRX’ website.
One additonal feature of DAB, much worthwhile to be mentioned, is the so-called “Guard Interval“. It guarantees that all transmitters involved in an Singe-Frequency Network, with their individual stations distinguishable only by their TII codes, can all transmit on exactly the same frequency – whereby the relative distances can be up to approx. 75km apart without interfering with each other. This has the consequence that e.g. the Bundesmux (5C – DR Deutschland) needs only one frequency nation-wide, which is e.g. selected once in the car and then works in the whole republic, not requiring any re-tuning by the driver. By the way, all locations of a block stored in the database can be displayed in QIRX with one mouse click.
Caveat: “Threshold” is as sensitive, as it is sensible. Too low a threshold may result in errors, too high a threshold may miss some transmitters. It is a good idea to start at a threshold allowing only one or two transmitters coming through, and then reduce this threshold by carefully checking the results for probability (etc. by their distance).
At some locations, there may occure a collision of the same sub-ID from different transmitters. This can be de-fuddled by QIRX’s function “Show Collisions for Sub ID”, but this is beyond this mere introduction. I have also to skip many more interesting applications of this software, e.g. using it for multipath detection by carefully observing the spectrum and measuring its deviations from a near-perfect brick-like shape – so that you can even calculate the delay caused by this effect.
We all have to be indebted to Clemens not only for his smart achievement in writing QIRX software, but also for his explanations and examples on his website! He also helped in explaining some details for this text.
P.S.: Don’t miss the second part of this blog, showing some examples of analyzing QIRX’ logged data!
P.P.S: The best: the QIRX story isn’t over with just DAB. It features also a ADS-B decoder for those flight messages on 1.090MHz, drawing them on a map, and filing them. I will come back to this also stunning feature soon – stay tuned!