Shmoocon: Delightful Doppler Direction Finding With Software Defined Radio

When it comes to finding what direction a radio signal is coming from, the best and cheapest way to accomplish the task is usually a Yagi and getting dizzy. There are other methods, and at Shmoocon this last weekend, [Michael Ossmann] and [Schuyler St. Leger] demonstrated pseudo-doppler direction finding using cheap, off-the-shelf software defined radio hardware.

The hardware for this build is, of course, the HackRF, but this pseudo-doppler requires antenna switching. That means length-matched antennas, and switching antennas without interrupts or other CPU delays. This required an add-on board for the HackRF dubbed the Opera Cake. This board is effectively an eight-input antenna switcher using the state configurable timer found in the LPC43xx found on the HackRF.

The key technique for pseudo-doppler is basically switching between an array of antennas mounted in a circle. By switching through these antennas very, very quickly — on the order of hundreds of thousands of times per second — you can measure the Doppler shift of a transmitter.

However, teasing out a distinct signal from a bunch of antennas virtually whizzing about isn’t exactly easy. If you look at what the HackRF an Opera Cake receive on a waterfall display, you’ll find a big peak around where you expect, and copies of that signal trailing off, separated by whatever your antenna switching frequency is. This was initially a problem for [Schuyler] and [Ossmann]’s experiments. Spinning the antennas at 20 kHz meant there was only 20 kHz difference in these copies, resulting in a mess that can’t be decoded. The solution was to virtually spin these antennas much faster, resulting in more separation, and a clean signal.

There are significant challenges when it comes to finding the direction of modern radio targets. Internet of Things things sometimes have very short packet duration, modulation interferes with antenna rotation, and packet detection must maintain the phase. That said, is this technique actually able to find the direction of IoT garbage devices? Yes, the demo on stage was simply finding the direction of one of the wireless microphones for the talk. It mostly worked, but the guys have some ideas for the future that would make this technique work a little better. They’re going to try phase demodulation instead of only frequency-based demodulation. They’re also going to try asymmetric antenna arrays and pseudorandom antenna switching. With any luck, this is going to become an easy and cheap way to do pseudo-doppler direction finding, all enabled by a few dollars in hardware and a laser-cut jig to hold a few antennas.

Measuring Airflow in an HVAC System

[Nubmian] wrote in to share his experiments with measuring airflow in an HVAC system. His first video deals with using with ultrasonic sensors. He found an interesting white paper that described measuring airflow with a single-path acoustic transit time flow meter. The question was, could he get the same effects with off-the-shelf components?

[Nubmian] created a rig using a pair of typical ultrasonic distance sensors. He detached the two transducers from the front of the PCB. The transducers were then extended on wires, with the “send” capsules together pointing at the “receive” capsules. [Nubmian] set the transducers up in a PVC pipe and blew air into it with a fan.

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Homemade 6 GHz Radar, v3

The third version of [Henrik Forstén] 6 GHz frequency-modulated continuous wave (FMCW) radar is online and looks pretty awesome. A FMCW radar is a type of radar that works by transmitting a chirp which frequency changes linearly with time. Simple continuous wave (CW) radar devices without frequency modulation cannot determine target range because they lack the timing mark necessary for accurately time the transmit and receive cycle in order to convert this information to range. Having a transmission signal modulated in frequency allows for the radar to have both a very high accuracy of range and also to measure simultaneously the target range and its relative velocity.

Like the previous versions, [Henrik] designed a four-layer pcb board and used his own reflow oven to solder all the ~350 components. This process, by itself, is a huge accomplishment. The board, much bigger than the previous versions, now include digital signal processing via FPGA.

[Henrik’s] radar odyssey actually started back in 2014, where his first version of the radar was detailed and shared in his blog. A year later he managed to solve some of the issues he had, design a new board with significant improvements and published it again. As the very impressive version three is out, we wonder what version four will look like.

In the video of [Henrik] riding a bicycle in a circle in front of the radar, we can see the static light posts and trees while he, seen as a small blob, roams around:

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Doppler Module Teardown Reveals the Weird World of Microwave Electronics

Oscillators with components that aren’t electrically connected to anything? PCB traces that function as passive components based solely on their shape? Slots and holes in the board with specific functions? Welcome to the weird and wonderful world of microwave electronics, brought to you through this teardown and analysis of a Doppler microwave transceiver module.

We’ve always been fascinated by the way conventional electronic rules break down as frequency increases. The Doppler module that [Kerry Wong] chose to pop open, a Microsemi X-band transceiver that goes for about $10 on eBay right now, has vanishingly few components inside. One transistor for the local oscillator, one for the mixer, and about three other passives are the whole BOM. That the LO is tuned by a barium titanate slug that acts as a dielectric resonator is just fascinating, as is the fact that PB traces can form a complete filter network just by virtue of their size and shape. Antennas that are coupled to the transceiver through an air gap via slots in the board are a neat trick too.

[Kerry] analyzes all this in the video below and shows how the module can be used as a sensor. If you need a little more detail on putting these modules to work, we’ve got some basic circuits you can check out.

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Fail of the Week: Tracking Meteors with Weather Radio

It’s not hard to detect meteors: go outside on a clear night in a dark place and you’re bound to see one eventually. But visible light detection is limiting, and knowing that meteors leave a trail of ions means radio detection is possible. That’s what’s behind this attempt to map meteor trails using broadcast signals, which so far hasn’t yielded great results.

Passing jet’s Doppler signature

The fact that meteor trails reflect radio signals is well-known; hams use “meteor bounce” to make long-distance contacts all the time. And using commercial FM broadcast signals to map meteor activity isn’t new, either — we’ve covered the “forward scattering” technique before. The technique requires tuning into a frequency used by a distant station but not a local one and waiting for a passing meteor to bounce the distant signal back to your SDR dongle. Capturing the waterfall display for later analysis should show characteristic patterns and give you an idea of where and when the meteor passed.

[Dave Venne] is an amateur astronomer who turns his eyes and ears to the heavens just to see what he can find. [Dave]’s problem is that the commercial FM band in the Minneapolis area that he calls home is crowded, to say the least. He hit upon the idea of using the National Weather Service weather radio broadcasts at around 160 MHz as a substitute. Sadly, all he managed to capture were passing airplanes with their characteristic Doppler shift; pretty cool in its own right, but not the desired result.

The comments in the RTL-SDR.com post on [Dave]’s attempt had a few ideas on where this went wrong and how to improve it, including the intriguing idea of using 60-meter ham band propagation beacons. Now it’s Hackaday’s turn: any ideas on how to fix [Dave]’s problem? Sound off in the comments below.

Hackaday Prize Entry: Heart Failure Detection Device

Early and low-cost detection of a Heart Failure is the proposal of [Jean Pierre Le Rouzic] for his entry for the 2017 Hackaday Prize. His device is based on a low-cost Doppler device, like those fetal Doppler devices used to listen an unborn baby heart, feeding a machine learning algorithm that could differentiate between a healthy and an unhealthy heart.

The theory behind it is that a regular, healthy heart tissue has a different acoustic impedance than degenerated tissue. Based on the acoustic impedance, the device would classify the tissue as: normal, degenerated, granulated or fibrous. Each category indicates specific problems mostly in connective tissues.

There are several advantages to have a working device like the one [Rouzic] is working on. To start, it would be possible to use it at home, without the intervention of a doctor or medical staff. It seems to us that would be as easy as using a blood pressure device or a fetal Doppler. It’s also relatively cheap (estimated under 150$) and it needs no gel to work. We covered similar projects that measure different heart signals, like Open Source electrocardiography, but ECG has the downfall that it requires attaching electrodes to the body.

One interesting proposed feature is that what is learn from a single case, is sent to every devices at their next update, so the devices get ‘smarter’ as they are used. Of course, there are a lot of ways for this to go wrong, but it’s a good idea to begin with.

The Right Circuit Turns Doppler Module into a Sensor

Can you buy a working radar module for $12? As it turns out, you can. But can you make it output useful information? According to [Mathieu], the answer is also yes, but only if you ignore the datasheet circuit and build this amplification circuit for your dirt cheap Doppler module.

The module in question is a CDM324 24-GHz board that’s currently listing for $12 on Amazon. It’s the K-band cousin of the X-band HB100 used by [Mathieu] in a project we covered a few years back, but thanks to the shorter wavelength the module is much smaller — just an inch square. [Mathieu] discovered that the new module suffered from the same misleading amplifier circuit in the datasheet. After making some adjustments, a two-stage amp was designed and executed on a board that piggybacks on the module with a 3D-printed bracket.

Frequency output is proportional to the velocity of the detected object; the maximum speed for the sensor is only 14.5 mph (22.7 km/h), so don’t expect to be tracking anything too fast. Nevertheless, this could be a handy sensor, and it’s definitely a solid lesson in design. Still, if your tastes run more toward using this module on the 1.25-cm ham band, have a look at this HB100-based 3-cm band radio.

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