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It stands to reason, that should you wish to communicate with a satellite, whatever antenna you use should point at that satellite. Some of us have done this by hand, following the bright dot of the space station in the night sky. Still, for anything more serious than trying to catch a fleeting SSTV image, a more robust solution is called for. In other words, a motorized antenna rotator, and AntRunner from [Wuxx] is just the ticket. Better still, it’s portable for those /p operating sessions off the beaten track.
The rotator itself is an az-el design with a couple of geared stepper motors. The full mechanism design has been published, but it shouldn’t be too difficult to copy. The interesting part is the controller and software, which can work with Gpredict, Hamlib, and SDR for automated satellite tracking. The controller is as straightforward as an ESP32 running the ESP port of GRBL.
So here’s a portable antenna rotator that’s accessible and widely supported, what’s not to like? As you might expect though, it’s not the first we’ve seen. In fact, the 2014 Hackaday Prize was won by SatNOGs, which includes a 3D printed antenna positioner.
Thanks [Abe Tusk] for the tip!
In the “old” days, people were used to the idea that radio communication isn’t always perfect. AM radio had cracks and pops and if you had to make a call with a radiophone, you expected it to be unreliable and maybe even impossible at a given time. Modern technology, satellites, and a host of other things have changed and now radio is usually super reliable and high-fidelity. Usually. However, a magnitude 7.9 solar flare this week reminded radio users in Africa and the Middle East that radio isn’t always going to get through. At least for about an hour.
It happened at around 10 AM GMT when that part of the world was facing the sun. Apparently, a coronal mass ejection accompanied the flare, so more electromagnetic disruption may be on its way.
The culprit seems to be an unusually active sunspot which is expected to die down soon. Interestingly, there is also a coronal hole in the sun where the solar wind blows at a higher than usual rate. Want to keep abreast of the solar weather? There’s a website for that.
We’ve pointed out before that we are ill-prepared for technology blackouts due to solar activity, even on the power grid. The last time it happened, we didn’t rely so much on radio.
Image/Video via Helioviewer.org
Amateur radio operators have played a longstanding game of “Will It Antenna?” If there’s something even marginally conductive and remotely resonant, a ham has probably tried to make an antenna out of it. Some of these expedient antennas actually turn out to be surprisingly effective, but as we can see from this in-depth analysis of the characteristics of tape measure antennas, a lot of that is probably down to luck.
At first glance, tape measure antennas seem to have a lot going for them (just for clarification, most tape measure antennas use only the spring steel blade of a tape measure, not the case or retraction mechanism — although we have seen that done.) Tape measures can be rolled up or folded down for storage, and they’ll spring back out when released to form a stiff, mostly self-supporting structure.
But [fvfilippetti] suspected that tape measures might have some electrical drawbacks, thanks to the skin effect. That’s the tendency for current to flow on the outside of a conductor, which at lower frequencies on conductors with a round cross-section turns out to be not a huge problem. But in a thin, rectangular conductor, a little finite element method magnetics (FEMM) analysis revealed that most of the current is carried in very small areas, resulting in high electrical resistance — an order of magnitude greater than a round conductor. Add in the high permittivity of the carbon steel material of the blade, and you end up something more like what [fvfilippetti] calls “a tape measure dummy load.
One possible solution: stripping the paint off the blade and copper plating it. It’s not clear if this was tried; we’d think it would be difficult to accomplish, but not impossible — and surely worth a try.
The average person’s perception of a ham radio operator, assuming they even know what that means, is more than likely some graybeard huddled over the knobs of a war-surplus transmitter in the wee small hours of the morning. It’s a mental image that, admittedly, isn’t entirely off the mark in some cases. But it’s also a gross over-simplification, and a generalization that isn’t doing the hobby any favors when it comes to bringing in new blood.
In reality, a modern ham’s toolkit includes a wide array of technologies that are about as far away from your grandfather’s kit-built rig as could be — and there’s exciting new protocols and tools on the horizon. To ensure a bright future for amateur radio, these technologies need to be nurtured the word needs to be spread about what they can do. Along the way, we’ll also need to push back against stereotypes that can hinder younger operators from signing on.
On the forefront of these efforts is Amateur Radio Digital Communications (ARDC), a private foundation dedicated to supporting amateur radio and digital communication by providing grants to scholarships, educational programs, and promising open source technical projects. For this week’s Hack Chat, ARDC Executive Director Rosy Schechter (KJ7RYV) and Staff Lead John Hays (K7VE) dropped by to talk about the future of radio and digital communications.
Rosy kicked things off with a brief overview of ARDC’s fascinating history. The story starts in 1981, when Hank Magnuski had the incredible foresight to realize that amateur radio packet networks could benefit from having a dedicated block of IP addresses. In those early days, running out of addresses was all but unimaginable, so he had no trouble securing 16.7 million IPs for use by licensed amateur radio operators. This block of addresses, known as AMPRNet and then later 44Net, was administered by volunteers until ARDC was formed in 2011 and took over ownership. In 2019, the decision was made to sell off about four million of the remaining IP addresses — the proceeds of which went into an endowment that now funds the foundation’s grant programs.
So where does the money go? The ARDC maintains a list of recipients, which provides for some interesting reading. The foundation has helped fund development of GNU Radio, supported the development of an open hardware CubeSat frame by the Radio Amateur Satellite Corporation (AMSAT), and cut a check to the San Francisco Wireless Emergency Mesh to improve communications in wildfire-prone areas. They even provided $1.6 million towards the restoration of the MIT Radio Society’s radome and 18-foot dish.
Of all the recipients of ARDC grants, the M17 project garnered the most interest during the Chat. This community of open source developers and radio enthusiasts is developing a next-generation digital radio protocol for data and voice that’s unencumbered by patents and royalties. In their own words, M17 is focused on “radio hardware designs that can be copied and built by anyone, software that anyone has the freedom to modify and share to suit their own needs, and other open systems that respect your freedom to tinker.” They’re definitely our kind of folks — we first covered the project in 2020, and are keen to see it develop further.
John says the foundation has approximately $6 million each year they can dole out, and that while there’s certainly no shortage of worthwhile projects to support as it is, they’re always looking for new applicants. The instructions and guides for grant applications are still being refined, but there’s at least one hard requirement for any project that wants to be funded by the ARDC: it must be open source and available to the general amateur population.
Of course, all this new technology is moot if there’s nobody to use it. It’s no secret that getting young people interested in amateur radio has been a challenge, and frankly, it’s little surprise. When a teenager can already contact anyone on the planet using the smartphone in their pocket, getting a ham license doesn’t hold quite the same allure as it did to earlier generations.
The end result is that awareness among youth is low. During the Chat, one participant recounted how he had to put Netflix’s Stranger Things on pause so he could explain to his teenage son how the characters in the 1980s set show were able to communicate across long distances using a homemade radio. Think about that for a minute — in a show about nightmarish creatures invading our world from an alternate dimension, the hardest thing for this young man to wrap his head around was the fact a group of teenagers would be able to keep in touch with each other without the Internet or phone lines to connect them.
So its no surprise that John says the ARDC is actively looking for programs which can help improve the demographics of amateur radio. The foundation is looking to not only bring younger people onboard, but also reach out to groups that have been traditionally underrepresented in the hobby. As an example, he points to a grant awarded to the Bridgerland Amateur Radio Club (BARC) last year to bolster their youth engagement program. Funds went towards putting together a portable rig that would allow students to communicate with the International Space Station, and the development of hands-on workshops where teens will be able to launch, track, and recover payloads on a high altitude balloon. Let’s see them do that on their fancy new smartphone.
We want to not only thank Rosy Schechter and John Hays for taking part in this week’s Hack Chat, but everyone else at Amateur Radio Digital Communications for their efforts to support the present and future of amateur radio and digital communication.
The Hack Chat is a weekly online chat session hosted by leading experts from all corners of the hardware hacking universe. It’s a great way for hackers connect in a fun and informal way, but if you can’t make it live, these overview posts as well as the transcripts posted to Hackaday.io make sure you don’t miss out.
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[David], DL1DN, is an Amateur Radio enthusiast with a penchant for low-power (QRP) portable operations. Recently he was out and about, and found that 10 m propagation was wide open. Not discouraged by having forgotten his antenna, he kludges up a makeshift one using a 20 cm length of aluminum foil (see video demonstration below the break). [David] wasn’t completely unprepared, as he did have the loading coil for his portable 20 m antenna, but was missing the telescoping whip. He calculated the whip length should be around 20 cm for 10 m operation, and crinkles up a sheet of foil the approximate length. He tunes it to length by rolling the tip to shorten the “whip” until he gets an SWR minimum.
[David] describes this style of portable antenna in another video, using a more conventional telescoping whip as the radiating element. The loading coil is built from common PVC pipe and insulated wire. While these aren’t necessarily the most efficient antennas, they can do the trick when portability is a major concern. For a different approach, here’s a QRP Hackaday.io portable antenna project using a magnetic loop antenna. But for the ultimate in QRP, check out this transmitter we wrote about in 2013 that uses only voice power to operate.
What are some unusual items you’ve used as makeshift antennas? Let us know in the comments below. Thanks to [mister35mm] for submitting this to our tip line.
With music consumption having long ago moved to a streaming model in many parts of the world, it sometimes feels as though, just like the rotary telephone dial, kids might not even know what a radio was, let alone own one. But there was a time when broadcasting pop music over the airwaves was a deeply subversive activity for Europeans at least, as the lumbering state monopoly broadcasters were challenged by illegal pirate stations carrying the cutting edge music they had failed to provide. [Ringway Manchester] has the story of one such pirate station which broadcast across the city for a few years in the 1970s, and it’s a fascinating tale indeed.
It takes the form of a series of six videos, the first of which we’ve embedded below the break. The next installment is placed as an embedded link at the end of each video, and it’s worth sitting down for the full set.
The action starts in early 1973 when a group of young radio enthusiast friends, left without access to a station of their taste by Government crackdowns on ship-based pirate stations, decided to try their hand with a land-based alternative. Called Radio Aquarius, it would broadcast on and off both the medium wave (or AM) and the FM broadcast bands over the next couple of years. Its story is one of improvised transmitters powered by car batteries broadcasting from hilltops, woodland, derelict houses, and even a Cold War nuclear bunker, and develops into a cat-and-mouse game between the youths and the local post office agency tasked with policing the spectrum. Finally having been caught once too many times, they disband Radio Aquarius and go on to careers in the radio business.
The tale has some tech, some social history, and plenty of excitement, but the surprise is in how innocent it all seems compared to the much more aggressively commercial pirate stations that would be a feature of later decades. We’d have listened, had we been there!
Not only pirate radio has made it to these pages, we’ve also brought you pirate TV!
Modern oscilloscopes and digitizers are getting better and better. Higher bandwidth, better vertical resolution, and longer acquisition memories. Not to mention more firmware tools for application-specific measurements. With all these advanced analysis capabilities it is sometimes hard to remember some very old and simple rules that can improve the accuracy and precision of your measurements. Here are a few good ideas to help.
Use the full dynamic range of your instrument’s front end
Digital instruments feed their input signals to an analog-to-digital converter (ADC). The dynamic range of the ADC is related to its number of bits of resolution. The instrument matches the input signal to the ADC input voltage range using attenuators or amplifiers. If the input to the ADC is less than its input range, it reduces the total dynamic range of the ADC. This can happen when users set up multiple traces on the screen.
Some oscilloscopes and digitizers display software only offer a single display grid. If you try and display more than one signal trace at full dynamic range, the signals overlap, making it hard to view them. Most people faced with this problem reduce the vertical scaling of each channel. If you have four traces, just increase the volts per division setting by a factor of four. Each trace now occupies only a quarter of the screen and all four traces fit on the screen with no overlap. Problem solved? Not really. You just reduced the dynamic range by two bits, you made your eight-bit oscilloscope a six-bit oscilloscope. You attenuated the signal, but the internal noise of the instrument is the same, the signal-to-noise ratio is now worse by two bits. Figure 1 shows the effect of the loss of dynamic range.
Figure 1 An example of the decrease in signal-to-noise ratio due to reducing the signal amplitude in order to fit multiple traces on a single grid.
The bottom grid shows the original signal acquired a 50mV/division. The top trace shows the trace acquired at one quarter of the full screen or 200mV/division. If you vertically expand the attenuated trace and display it at the original 50mV/division, the vertical noise has increased significantly as you can tell from the thickening of the displayed trace. Measurements made on the attenuated trace will have increased uncertainty due to a poorer signal-to-noise ratio. This is not a problem for an oscilloscope or digitizer that has multiple grid displays, each grid displays the signal at full dynamic range and multiple signals can be compared, each in its own grid. If you don’t have access to a multiple grid oscilloscope, make sure that any measurements are made on the full amplitude signals, reserve the attenuated signal for visual comparisons only.
Improve dynamic range and measurement accuracy by eliminating noise
Use signal processing in the form of averaging or filtering to reduce noise, improve dynamic range and measurement accuracy. Ensemble averaging, where the nth samples of each acquisition are averaged together over multiple acquisitions, reduces Gaussian noise proportional to the square root of the number of averaged signals. This can bring a low level signal out of background noise for better measurements. It does require multiple acquisitions.
For a single acquisition, you can reduce noise by bandwidth limiting the signal. The improvement of dynamic range is proportional to the square root of the bandwidth reduction. Reduce the bandwidth by a factor of four to achieve a two-to-one improvement in dynamic range. This assumes that the signal has a low bandwidth and is not affected by the bandwidth reduction. Figure 2 shows the improvement that can be achieved using either averaging or filtering.
Figure 2 Averaging multiple acquisitions or filtering a single acquisition can improve the dynamic range of the acquisition by eliminating noise.
The acquired signal is an exponentially damped sine wave. The top trace shows a raw acquisition. Note that the signal disappears into the noise about three quarters of the way across the screen. The center trace shows the average of multiple acquisitions. In the bottom trace, a Gaussian low pass filter has been applied to the acquired signal. Both averaging and filtering reduce the noise and improve the dynamic range of the measurement. The signal is clearly discernible after either type of signal processing.
Improving the accuracy of cursor measurements
Cursors are vertical and/or horizontal lines that can be moved over the oscilloscope or digitizer display to mark significant points on a waveform. Cursor readouts show the time or amplitude of the waveform at the cursor location as shown in Figure 3. The waveform is a keyed RF carrier and the horizontal relative cursors are used to measure the width of the RF burst. This is a measurement that cannot be made with the instrument’s automatic measurement parameters. The cursor horizontal readout appears in the lower right-hand corner under the timebase annotation box, it reads 8.06275 µs.
Figure 3 Horizontal relative cursors are used to measure the duration of an RF pulse burst.
Is that really the duration of the burst? The answer is no. This waveform has two million samples in the acquisition. The horizontal screen resolution is 1920 pixels. So, it’s obvious that not all the samples are shown on the screen. Instrument manufacturers apply compaction algorithms to reduce the number of displayed points. They manage to show significant points like peaks but there is still a lot that you can’t see unless you expand the display.
A more accurate way to make this measurement is the used the zoom traces to horizontally expand the waveform at the start and end of the RF burst as shown in Figure 4.
Figure 4 Using zoom traces to make more accurate placements of the cursors at the first and last sample points of the burst.
Zoom traces Z1 and Z2 horizontally expand the beginning and ending of the burst. The sample counts in the zoom traces are smaller than the screen resolution so the compaction algorithm is not used. The cursors track on the acquired signal and the zoom traces. The cursor on zoom trace Z1 (yellow trace) marks the beginning of the RF burst which starts at a zero crossing. The cursor on zoom trace Z2 (red trace) marks the end of the burst. The cursor horizontal readout shows the burst length as 8.33295 ms, a more accurate result.
Built-in measurement parameters
Oscilloscope and digitizer support software offers built-in measurement parameters. Most oscilloscopes include about twenty or more common measurement parameters like amplitude, frequency, rise time, and fall time to mention a few. Application-specific software packages can increase the number of available parameters to over a hundred. The standard parameter measurements are usually based on IEEE standard 181 which employs statistical techniques to make the measurements on pulse waveforms as shown in Figure 5.
Figure 5 IEEE Standard 181 bases pulse measurement parameters on a statistical determination of the top and base values of a measured pulse.
The amplitude values of the pulse top and base are determined by forming a histogram of the acquired samples of the waveform, this is shown as an inset on the right of the screen. A square wave or pulse waveform will have a histogram with two distinct peaks. The average or mean values of the upper histogram peak is called the “top”. The mean of the lower valued peak is called the “base” of the waveform. Using the statistical mean of many pulse measurements suppresses the effects of waveform aberrations like noise, overshoot, and ringing. The pulse amplitude is the difference between the top and base. The maximum value of the waveform minus the top is the positive overshoot. Likewise, the difference between the waveform minimum value and the base is the negative overshoot. The pulse width is the time difference between the leading and trailing edges crossing the mid-amplitude or median between the top and base. The peak-to-peak value of the waveform is the difference between the maximum and minimum amplitudes. The transition time measurements, like rise and fall time, measure the time to transition from 90% to 10% of the pulse amplitude. If the waveform is not a pulse, the measurement engine sees that because the waveform histogram has more or less than the two peaks that define a pulse. In that case, the amplitude measurement reverts to a peak-to-peak measurement and indicates the fact that the waveform is not a pulse using a measurement status icon under the parameter readout.
In almost all cases, the measurements made using measurement parameters are far more accurate than those made using cursors. They are also made automatically saving a great deal of time.
Measurement Statistics
How do instrument measurements vary from measurement to measurement? Measurement statistics answer that question. Many instruments include statistics reporting along with the basic measurement parameters as shown in Figure 6.
Figure 6 Measurement statistics record how measurement values vary over multiple measurements showing the last value, mean, minimum, maximum, standard deviation, and total population.
Some oscilloscopes include all instance measurements. Time-related measurements, like frequency and width, report one value for each cycle of the measured waveform. If you have 100 cycles of a signal on the screen, the measurement engine adds 100 measurements for each acquisition. Amplitude-related measurements only add a single value per acquisition. You can acquire a good many measurement values over many acquisitions. Measurement statistics provide very useful views of this data. The table under the waveform display, shown expanded in the blue box, lists the last value measured in the acquisition, the mean values of all the acquired values, the minimum and maximum values of the set, the standard deviation of the set, and the total population of all the measurements. It also includes a status indicator and an iconic histogram of all the measurement values.
The amplitude measurement reports that 11,873 values are included in the statistics. The mean or average value is 237.5457 mV. The mean value is reported with a higher resolution than the last value because the mean is an averaged value. As we saw in the waveform, averaging the averaging process improves the vertical resolution of the measurement, the same thing happens if you average multiple measurements, hence the more significant figures in the mean value.
The largest value is 241.5 mV reported as the maximum, the smallest value, minimum, is 234.8mV. These values can help detect transient events that occur during the acquisitions. Other tools can plot measured values versus time to see when transient events occur and match them in time with possible sources.
The standard deviation describes the distribution of the measured values about the mean, in this case is it 826 µV. The mean and standard deviation are useful in understanding the distribution of the measured values as is the iconic histogram. The iconic histogram can be expanded to view the full-sized histogram for a more detailed analysis with its own set of histogram measurements. All of these measurement tools help understand the dynamics of the particular measurements. A knowledge of the distribution of measurements enables you to establish test limits for signals.
Conclusions
These tools and techniques can help improve the measurement accuracy and reliability of your instruments. Other tricks can be gleaned from manufacturer’s webinars and application notes. The more you learn about your instrument, the more accurate and reliable your measurement results will be.
Arthur Pini is a technical support specialist and electrical engineer with over 50 years of experience in electronics test and measurement.