SignalsEverywhere: Decoding HD Radio with an RTL-SDR

Corrosive (KR0SIV) from the SignalsEverywhere YouTube channel has uploaded a new video that explains and shows HD radio being decoded with an RTL-SDR.

If you are in the USA, you might recognize HD (Hybrid Digital) Radio (aka NRSC-5) signals as the rectangular looking bars on the frequency spectrum that surround common broadcast FM radio signals. These signals only exist in the USA and they carry digital audio data which can be received by special HD Radio receivers. Back in June 2017 we posted about how [Theori] was able to piece together a full HD Radio software audio decoder that works in real time. Later developments saw additional data such as traffic data and weather info extracted from HD Radio too.

Corrosive's video also shows a comparison between analog and HD Radio audio. We note that the "HD" doesn't stand for high definition, so audio quality is not really better than the analog stream. He also notes that the HD Radio data stream can contain multiple audio channels, and often they are not the same as the analog station it surrounds. One example he shows is a Simulcast AM radio station being rebroadcast via HD Radio.

HD Radio RTL-SDR Decoding vs Analog Radio

Leif Continues his Comparisons of the Airspy HF+ Discovery, RSP1, Perseus and more SDRs (Parts 3,4,5)

Leif (sm5bsz)'s series comparing the Airspy HF+ Discovery against various other SDRs such as the Perseus, SDRplay RSP1, Airpsy HF+ Dual, Airspy + SpyVerter and AFEDRI SDR-Net continues again, with parts 3, 4, and 5 now having been uploaded to YouTube. In previous posts we covered parts 1 and 2.

The comparisons are very technically inclined, so may be difficult to follow for those unfamiliar with radio theory. We have highlighted the time stamps where he discusses the results.

In conclusion, for all tests the Perseus always comes out on top, with the HF+ Discovery coming a close second. Generally third best is the HF+ Dual, then the AFEDRI, followed by the Airspy+SpyVerter and RSP1.

Part 3: Here performance with real antenna signals is compared. Attenuators are used to make the noise figure 26 dB of all radios at the output of the 7 port resistive splitter. This video is for dynamic range on 7.2 MHz.

Results @ 30:20

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Part 4: Here performance with real antenna signals is compared. Attenuators are used to make the noise figure 27 dB of all radios at the output of the 7 port resistive splitter. This video is for dynamic range on 14 MHz.

Results @ 16:04

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Part 5: Here here second order intermodulation is studied.

Results @ 13:07

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Watching Lightning Strikes on the Spectrum with an RTL-SDR

Over on YouTube user Tech Addict Attic has uploaded a video demonstrating what lightning strikes look like on the radio spectrum. To receive the pulses he uses an RTL-SDR and a simple wire antenna located on his roof. He notes that the pulses show up at HF frequencies, and continue all the way up to the broadcast FM band and above.

When lightning strikes it emits a wideband RF pulse that can be detected several miles away by radios. On a software defined radio spectrum display the pulse shows up as a quick horizontal blip. Detecting this blip is how lightning detection websites like blitzortung.org work, although they use their own radio hardware.

In the past we posted about another user who also demonstrated lightning pulses using his RTL-SDR V3.

Watching Lightning with an RTL-SDR

Fingerprinting Electronic Devices via their RF Emissions with an RTL-SDR and ImageMagick

Thank you to José Carlos Rueda for submitting his simple shell script that he uses for fingerprinting spurious RF emissions with an RTL-SDR, rtl_power, heatmap.py and imagemagick. The result is something like Disney's EM sense created with much simpler code.

It is well known that almost all electronic devices unintentionally emit unique spurious RF signals when in operation. By using an SDR like an RTL-SDR to record the spectra from electronic devices, it's possible to build up a database of known emissions. We can then detect when an electronic device is active by comparing the live spectrum to spectra stored in the database.

In a previous post we covered Disney's EM sense which is an experimental smart watch that automatically detects what electronic device the wearer is touching. With EM Sense they use an RTL-SDR and a database of raw pre-recorded spectrum data. To detect what the wearer is touching the live signal from the RTL-SDR is correlated against the database, and the closest match is returned.

José's script does something very similar, however instead of correlating with raw spectrum data he instead uses the waterfall image that is generated by rtl_power and heatmap.py. The rtl_power program allows an RTL-SDR to scan the frequency spectrum over a wider bandwidth by rapidly scanning ~2.4 MHz chunks of bandwidth at different frequencies. Heatmap.py is a program that turns the scanned data from rtl_power into a heatmap image of the spectrum.

To add an entry to the database, the electronic device is placed 7-8 centimeters away from the RTL-SDR, and a heatmap image recorded between 24 - 921 MHz is saved to disk. This can be repeated for multiple electronic devices. Each image will record the spurious signals from the electronic device, resulting in a unique heatmap image per electronic device.

Once the database has been created, you can then place any of the devices found in the database next to the RTL-SDR, and record a heatmap for 20-30s. That heatmap will then be compared against the images in the database using imagemagick which is an image analysis and manipulation library. The electronic device associated with the closest matching image in the database will be returned.

In his experiments he tested various electronic devices like an iPhone and was able to successfully determine when it was nearby.

Various electronic device spectra waterfall images recorded in the database
Various electronic device spectra waterfall images recorded in the database

Measuring the USB Power Consumption of Various Software Defined Radios

Over on his YouTube channel icholakov has uploaded a video comparing the USB power consumption of various software defined radios. In his tests he uses an inline USB current meter and compares a Perseus, RSP1, RSP1A, Airspy HF+, Airspy HF+ Discovery, RTL V3, Nooelec RTL Mini, Hauppauge 955Q, Flightaware RTL.

If you're only interested in the summary table, then this can be found at 05:49 in the video.

Generally SDRs with better performing tuners and more amplifiers will have higher power requirements, although current consumption can't solely be used to judge performance as some SDRs like the SDRplay make extensive use of filtering to overcome RX performance issues in their tuner. The RTL-SDR V3 and FlightAware dongles have slightly higher current draw compared to the Mini RTL-SDR as they contain an additional HF amplifier and ADS-B amplifier respectively. Lower power consumption may be useful when used with batteries and mobile phones.

Nine SDR Receivers power consumption comparison - how much power does your SDR consume?

Electrosense: RTL-SDR Based Crowd Sourced Spectrum Monitoring with a DC to 6 GHz Up/Downconverter

Recently we came across Electrosense which is an interesting open source project that aims to deploy radio spectrum sensors worldwide in order to analyze and understand radio spectrum usage. This information could be extremely valuable in order to make more efficient use of the limited radio spectrum, and for detecting sources of interference and illegal transmissions. The hardware that Electrosense uses consists of just an RTL-SDR, Raspberry Pi, antenna and an optional GPS for time synchronization.

The ElectroSense network is a crowd-sourcing initiative to collect and analyse spectrum data. It uses small radio sensors based on cheap commodity hardware and offers aggregated spectrum information over an open API.

The initiative's goal is to sense the entire spectrum in populated regions of the world and to make the data available in real-time for different kinds of stakeholders which require a deeper knowledge of the actual spectrum usage.

ElectroSense is an open initiative in which everyone can contribute with spectrum measurements and access the collected data.

High-level overview of the Electrosense network: Low-cost sensors collect spectrum information which are sent to the Electrosense backend. Different algorithms are run on the collected information in the backend and the results of these algorithms are provided to the users as a service through an open API. Users can develop their own applications from the spectrum information retrieved using the API.
Overview of the Electrosense network

There are already several spectrum sensing projects in the works by big companies like GoogleMicrosoft, and IBM, but these only cover a small portion of the spectrum, or use high cost sensing stations limiting their ability to be deployed on a wide scale. Electrosense solves these problems by using low cost RTL-SDRs, and a crowd sourcing paradigm.

At the time of writing there are 103 sensors registered to the Electrosense network, with 23 being online, most of which are in Europe. Once you register an account on their site, you can browse the active sensors. Clicking on the spectrum button for a sensor brings up a live spectrum graph. For example in the screenshot below we access the data from an RTL-SDR + downconverter sensor in Madrid. We're able to see a live wideband 20 MHz to 6 GHz spectrum scan, and graphs of frequency occupancy rates.

Electrosense Active Sensors
Electrosense Active Sensors
Electrosense Spectrum Scan and Occupancy Graphs
Electrosense Spectrum Scan and Occupancy Graphs

In addition to the standard SDR hardware being used, they've also designed a very interesting open hardware/source DC to 6 GHz up/downconverter board. The board is USB controlled, and switches between the upconverter for the lower HF bands, pass through for receiving DC- 1.6 GHz, and the downconverter for receiving up to 6 GHz. It has a 20 MHz output bandwidth which means that wide band SDRs can also make use of it.

Electrosense Up/Downconverter
Electrosense Up/Downconverter

The Electrosense website notes that anyone can host a sensor, and if you meet their criteria (permanent internet connection, ethernet connectivity and a low interference location) you can apply for a free kit. If you aren't selected for a free kit, then the Jetvision store based in Europe is selling Electrosense kits that include an RTL-SDR Blog V3, Raspberry Pi 3, power supply, SD card with preinstalled Electrosense software, and either our multipurpose dipole antenna, or a wideband discone with 15m of low loss cable for roof mounting.

The Electrosense team have been working hard on this project and have already published several related papers and a magazine article about the Electrosense network and it's use cases. One interesting paper discusses a method for decoding wideband signals using a network of non-coherent RTL-SDRs. Another paper discusses using using deep learning for automatic signal classification. The full list of publications can be found on their publications page.

If you're interested in this type of crowd sourced spectrum project, then you might also want to take a look at the KiwiSDR which is a networked 0 - 30 MHz SDR. Multiple crowd sourced KiwiSDR's can be used in a TDoA calculation for determining transmitter locations.

Building An Open Source SDR Based Hydrogen Line Radio Telescope

Over on Reddit we've seen a post by u/ArtichokeHeartAttack who has been working on a hydrogen line radio telescope, based on an RTL-SDR dongle and horn antenna designs by the DSPIRA program, and the Open Source Radio Telescopes website (site appears to be down, linked to the archive.org copy). [u/ArtichokeHeartAttack] has documented their radio telescope building journey, providing a comprehensive top-level document that is able to point interested people in the right direction towards understanding and building their own Hydrogen line radio telescope.

Briefly, their build consists of a horn antenna and reflector designed for the 1,420.4 MHz Hydrogen line frequency. The horn is built out of a few pieces of lumbar, metallic house wall insulation sheets and aluminum tape. The feed is made from a tin can and piece of wire. In terms of radio hardware, they used an Airspy SDR, GPIO labs Hydrogen Line Filter + LNA, and 2x Uputronics Wide band preamps, and a Minicircuits VBF-1445+ filter. For software processing, they used a GNU Radio flowgraph to integrate and record the spectrum.

The results show that they were able to achieve a good hydrogen line peak detection, and they were able to measure the galactic rotation curve doppler shift, and tangent points which prove that we do in fact live in a spiral galaxy.

The Finished Hydrogen Line SDR Based Horn Radio Telescope Antenna
The Finished Hydrogen Line SDR Based Horn Radio Telescope Antenna

Leif Continues his Comparisons of the Airspy HF+ Discovery, RSP1, Perseus and More SDRs

Leif (SM5BSZ) is fairly well known in the SDR community for doing very indepth technical tests of various SDR receivers over on his YouTube channel. Recently he's released part two of a series where he compares the new Airspy HF+ Discovery against various other SDRs such as the Perseus, SDRplay RSP1, Airpsy HF+ Dual, Airspy + SpyVerter and AFEDRI SDR-Net. In the first video he studied the blocking and second order intermodulation effects of each SDR using signal generators. We summarized those results in this previous post.

In the new video Leif compares the dynamic range of each SDR using real HF antenna signals at 7.2 MHz. In order to create a fair test of dynamic range, appropriate attenuation is added to each receiver in order to make their noise figures equivalent, so that the incoming signal strength is the same for each SDR.

The first set of dynamic range results is summarized at time 08:14, and these results show the dynamic range comparisons for strong night time signals. Again like in the other videos the Perseus is used as the reference SDR since it is always the best. The tests show that the HF+ Discovery trails behind the Perseus by only -3dB, followed by the HF+ Dual at -10dB, AFEDRI at -15dB, Airspy+SpyVerter at -18dB and finally the RSP1 at -23dB.

The second set of results is summarized at 17:47 and this includes a day time dynamic range test. The rankings are very similar to the night time test.

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