Time was once that the amateur radio bands were an aurally predictable place. Spinning the dial up and down the bands, one heard familiar sounds – the staccato of Morse, the [Donald Duck] of sideband voice transmissions, and the occasional flute-like warble of radioteletype signals. Now, the ham bands are full of exotic signals encoding all manner of digital signals, each one with a unique sound and unique demodulation needs. What’s a ham to do?
Help is on the way. [José Carlos Rueda] has made progress toward automatically classifying unknown signals by modifying a Shazam-like app. Shazam is a popular smartphone app that listens to a few seconds of a song, creates an audio fingerprint of it, and searches a massive database of songs for a match. [Rueda] used a homebrew version of the app to search a SQL-lite database of audio fingerprints populated not with a playlist of popular music, but with samples from every known signal type in the Signal Identification Wiki. The database contains hashes for an FFT of each sample, which can be easily searched. With a five to ten second sample of a signal, captured either live over a microphone or from a recording, he is able to identify the signal automatically.
Whether it be the weird, dissonant wail of PSK-31 or the angry buzzing of PACTOR, the goings-on across the bands no longer have to remain a mystery. We really like the idea here, and wonder if it can be expanded upon to visually decode signals based on their waterfall signatures using TensorFlow. There are some waterfall examples in [Danie Conradie]’s excellent article on RF modulation that could get you started.
When you’re looking to add some wireless functionality to a project, there are no shortage of options. You really don’t need to know much of the technical details to make use of the more well-documented modules, especially if you just need to get something working quickly. On the other hand, maybe you’ve gotten to the point where you want to know how these things actually work, or maybe you’re curious about that cheap RF module on AliExpress. Especially in the frequency bands below 1 GHz, you might find yourself interfacing with a module at really low level, where you might be tuning modulation parameters. The following overview should give you enough of an understanding about the basics of RF modulation to select the appropriate hardware for your next project.
Three of the most common digital modulation schemes you’ll see in specifications are Frequency Shift Keying (FSK), Amplitude Shift Keying (ASK), and LoRa (Long Range). To wrap my mechanically inclined brain around some concepts, I found that thinking of RF modulation in terms of pitches produced by a musical instrument made it more intuitive.
And lots of pretty graphs don’t hurt either. Signals from two different RF dev boards were captured and turned into waterfall and FFT plots using a $20 RTL-SDR dongle. Although not needed for wireless experimentation, the RTL-SDR is an extremely handy debugging tool, even to just check if a module is actually transmitting. Continue reading “RF Modulation: Crash Course For Hackers”→
In a move guaranteed to send audiophiles recoiling back into their sonically pristine caves, two doctoral students at ETH Zurich have come up with an interesting way to embed information into music. What sounds crazy about this is that they’re hiding data firmly in the audible spectrum from 9.8 kHz to 10 kHz. The question is, does it actually sound crazy? Not to our ears, playback remains surprisingly ok.
You can listen to a clip with and without the data on ETH’s site and see for yourself. As a brief example, here’s twelve seconds of the audio presenting two versions of the same clip. The first riff has no data, and the second riff has the encoded data.
You can probably convince yourself that there’s a difference, but it’s negligible. Even if we use a janky bandpass filter over the 8 kHz -10 kHz range to make the differences stand out, it’s not easy to differentiate what you’re hearing:
The basic 16×2 LCD is an extremely popular component that we’ve seen used in more projects than we could possibly count. Part of that is because modern microcontrollers make it so easy to work with; if you’ve got an I2C variant of the display, it only takes four wires to drive it. That puts printing a line of text on one of these LCDs a step or two above blinking an LED on a digital pin on the hierarchy of beginner’s electronics projects.
The basic idea is to “blink” the 5 V line so quick that a capacitor on the LCD side can float the electronics over the dips in voltage. As long as one of the pins of the microcontroller is connected to the 5 V line before the capacitor, it will be able to pick up when the line goes low. With a high enough data rate and a large enough capacitor as a buffer, you’re well on the way to encoding your data to be displayed.
For the transmitting side, [Vinod] is using a Python script on his computer that’s sending out the text for the LCD over a standard USB to UART converter. That’s fed into a small circuit put together on a scrap of perfboard that triggers a MOSFET off of the UART TX line.
Hackers love to make music with things that aren’t normally considered musical instruments. We’ve all seen floppy drive orchestras, and the musical abilities of a Tesla coil can be ear-shatteringly impressive. Those are all just for fun, though. It would be nice if there were practical applications for making music from normally non-musical devices.
Thanks to a group of engineers at Case Western Reserve University in Cleveland, there is now: a magnetic resonance imaging machine that plays soothing music. And we don’t mean music piped into the MRI suite to distract patients from the notoriously noisy exam. The music is actually being played through the gradient coils of the MRI scanner. We covered the inner working of MRI scanners before and discussed why they’re so darn noisy. The noise basically amounts to Lorenz forces mechanically vibrating the gradient coils in the audio frequency range as the machine shapes the powerful magnetic field around the patient’s body. To turn these ear-hammering noises into music, the researchers converted an MP3 of [Yo Yo Ma] playing [Bach]’s “Cello Suite No. 1” into encoding data for the gradient coils. A low-pass filter keeps anything past 4 kHz from getting to the gradient coils, but that works fine for the cello. The video below shows the remarkable fidelity that the coils are capable of reproducing, but the most amazing fact is that the musical modification actually produces diagnostically useful scans.
Our tastes don’t generally run to classical music, but having suffered through more than one head-banging scan, a half-hour of cello music would be a more than welcome change. Here’s hoping the technique gets further refined.
We can say one thing for [bitluni]: the BOMs for his projects, like this ESP32 AM radio transmitter, are always on the low side. That’s because he leverages software to do jobs traditionally accomplished with hardware, always with instructive results.
If you’re looking for a little more range for your low power transmitter and you’re a licensed amateur operator, you might want to explore the world of QRP radio.
AM, or amplitude modulation, was the earliest way of sending voice over radio waves. That makes sense because it is easy to modulate a signal and easy to demodulate it, as well. A carbon microphone is sufficient to crudely modulate an AM signal and diode — even a piece of natural crystal — will suffice to demodulate it. Outside of broadcast radio, most AM users migrated to single side band or SSB. On an AM receiver that sounds like Donald Duck, but with a little work, it will sound almost as good as AM, and in many cases better. If you want a better understanding of how SSB carries audio, have a look at [Radio Physics and Electronics] video on the subject.
The video covers the math of what you probably already know: AM has a carrier and two identical side bands. SSB suppresses the carrier and one redundant side band. But the math behind it is elegant, although you probably ought to know some trigonometry. Don’t worry though. At the end of the video, there’s a practical demonstration that will help even if you are math challenged.