Sarah from the SignalsEverywhere YouTube channel is back this week with a video review and demonstration of our RTL-SDR Blog Active L-Band patch antenna, which is designed for receiving Inmarsat and Iridium satellites between 1525 - 1660 MHz with an RTL-SDR or other bias tee capable SDR.
In the video Sarah demonstrates the patch antenna in action running in SDR++, discusses some of the features and compares it against another patch antenna. She goes on to briefly show JAERO receiving and decoding an 8400bps AERO voice channel.
The patch is currently in stock in our store for $49.95 shipped worldwide, or on Amazon USA for US customers. We note that previous problems (as explained in our earlier post) with cracks in the plastic in the latest batch with grey enclosures have been resolved now, and units shipping now are without defect.
Just a few days ago we posted about Job Geheniau's success at radio imaging the Cygnus-X star forming region at 1424 MHz with a 1.9m radio telescope, an RTL-SDR and some additional filtering and LNAs.
Now in his latest post on Facebook Geneniau has also shown that he has successfully imaged Cassiopeia A with the same equipment. Cassiopeia A is a supernova remnant known for being the "brightest extrasolar radio source in the sky at frequencies above 1 GHz" [Wikipedia]. Geheniau writes:
A new observation from JRT. These are driftscans of Cassiopeia A to make a radio plot. Several driftscans are made last week and combined. Always nice to see whats possible with a 1.5-1.9 meter dish. 2 LNA's and a bandpass filter, connected to a RTL-SDR at 1424 MHz. Happy that I got Cygnus complex and now Cassiopeia A which is the second radio source which is possible to receive with this dish.
The dish is fully remote controlled 50 km away.
Job Geheniau - The Netherlands
Cassiopeia A Radio Imaged with an RTL-SDR and 1.9m dishJob's Radio Telescope
Over on Facebook Job Geheniau has posted results from his latest radio astronomy experiment which involves imaging the Cygnus-X star forming region at 1424 MHz with a 1.9m radio telescope, an RTL-SDR and some additional filtering and LNAs. In the past we've posted about Geheniau's previous work which involved imaging the entire Milky Way at 1420 MHz, and measuring the basis for the dark matter hypothesis with a similar process and the same equipment. His latest post reads:
Cygnus-X is a massive star-forming region in the constellation Cygnus at a distance of 1.4 kiloparsecs (4600 light-years) from the Sun.
Cygnus-X has a size of 200 parsecs and contains the largest number of massive protostars and the largest stellar association within 2 kiloparsecs of the Sun. Cyg X is also associated with one of the largest molecular clouds known, with a mass of 3 million solar masses. [Wikipedia]
The idea: To take a radio picture of the Cygnus complex (Cygnus A + Cygnus X) with my 1.9 meter radio telescope. Equipment: 1.5 - 1.9 meter radio telescope Mini Circuits LNA ZX60-ULN33+ Bandpass filter 1200-1700 MHz 2nd LNA RTL-SDR VirgoSoft
Implementation: Multiple 4-hour drift scans of the Cygnus complex and beyond. In order not to be affected by HI at 1420 MHz, measurements were made at 1424 MHz. At this frequency there is Synchrotron radiation and no neutral hydrogen emission. To be sure that no Milky Way synchrotron radiation is measured there would be no or hardly any measurable power change outside the Cygnus complex during the drift scan. This was also observed in these measurements and also confirmed earlier in test measurements.
A total of 7 drift scans of 4 hours were made at 1424 MHz. Because the start of the driftscan generates a lot of wrong data (the 'cooling down/warming up' of the RTL-SDR), this has been removed in the measurements. The measurement starts at 2000 seconds and is always aborted at 12000 seconds in post-processing.
7 shots from RA 19 to RA 22. The declination varied each observation from DEC 36 to 43 degrees.
Because not every driftscan was perfect (heavy clouds gave worse results anyway as well as wind/rain or rfi) a total of 15 measurements were done, of which 7 were thus acceptable enough for editing.
In the end JRT performed measurements from 24 September to 9 October. Patience is a good thing.
Results: By editing the driftscan data in Excel with Conditional Format (giving color to the data) the final result is a 'radio photo' of the complex.
Of course, in view of the dish diameter, the beam is 8 degrees and thus a somewhat rough image of the Cygnus complex is sketched here.
Job Geheniau - Netherlands.
Cygnus-X Imaged at 1424 MHz with an RTL-SDR based home radio telescope.
The idea behind the attack is that ethernet cables can act as an antenna, leaking signals at frequencies which can easily be sniffed by a SDR. The specific technique in the paper does not decode normal network traffic, instead it requires that malicious code which modulates a custom signal over the ethernet cable be installed on the PC first. The technique used appears to be similar to what the Etherify software by SQ5BPF uses, which modulates data in morse code by turning the network card on and off.
Receiving a signal modulated by the LanTenna malware
Thank you to Tomasz Lemiech for writing in and sharing with us the release of his new software "dumphfdl". Tomasz is the author of dumpvdl2 and also maintains RTLSDR-Airband. Regarding dumphfdl Tomasz writes:
dumphfdl is a multichannel HFDL decoder for Linux. HFDL (High Frequency Data Link) is a protocol used for radio communications between aircraft and a network of ground stations using high frequency (HF) radio waves. Thanks to the ability of short waves to propagate over long distances, HFDL is particularly useful in remote areas (eg. over oceans or polar regions) where other ground-based communications services are out of range. While many aircraft carriers prefer satellite communications these days, HFDL is still operational and in use.
Available HFDL decoding applications typically run on Windows and take an audio signal on input. The signal has to be delivered to the decoder via a physical cable from an external shortwave receiver or via a virtual cable from an SDR. This makes these apps inherently single-channel. This shortcoming does not apply to dumphfdl which interfaces directly with the SDR, so no pipes or virtual audio cables are needed. The program can decode multiple HFDL channels simultaneously, up to available CPU power and SDR bandwidth (there is no fixed channel count limit).
dumphfdl uses SoapySDR library (https://github.com/pothosware/SoapySDR) to communicate with the radio. Any HF-capable receiver for which a SoapySDR driver exists, should work. I have tested it briefly with an RTL-SDR v3 dongle in direct sampling mode. While I had a bit of a success with it, HFDL signals are often quite weak, so a real HF radio (like SDRPlay RSP1A or Airspy HF+) gives much better results (more decoded messages).
The program may log decoded messages to a file or send them over the network for external processing and storage.
HFDL messages often contain diagnostic data accompanied with aircraft position information. The program may extract this data from decoded messages and provide a positional data feed for external plane tracking apps (eg. Virtual Radar Server). An example screenshot from VRS is attached - taken after about 2 hours of decoding eight HFDL channels spread across three HFDL subbands: 6.6, 8.9, and 10.0 MHz with two dumphfdl instances on two radios - RSP1A and Airspy HF+. Definitely a nice way to expand the coverage of a home ADS-B radar :-)
Refer to the README.md file in the project repository for more details. The program is still under development, so new features and further improvements might be expected in subsequent releases.
dumphfdl - decoded aircraft positions plotted on a map
DragonOS is a ready to use Ubuntu Linux image that comes preinstalled with multiple SDR software packages. The creator Aaron also runs a YouTube channel showing how to use the various packages installed. In his latest video Aaron shows how to use the SDR4space.lite application to automatically log the spectrum with an RTL-SDR, as well as with an ANTSDR (PlutoSDR clone).
This video shows how to setup DragonOS Focal to detect spectrum activity with the SDR4space.lite application, RTLSDR, and ANTSDR/PlutoSDR. I then show how to setup both InfluxDB and Grafana, which are both used to accept and log incoming detected frequencies from the SDR4space.lite application and RTLSDR.
InfluxDB is an open-source time series database and Grafana is the open source analytics & monitoring solution. The two solutions combined allow a user to log activity from as many receivers as they'd like and then near time display incoming results in custom dashboards and panels.
This first video goes over the initial setup, to include creating a cron job for repeated frequency detection surveys, how to link the database and visual front end, and then how to create and customize your first dashboard and panel. Information to populate the database comes from two separate receivers in this demonstration, both from a remote RTLSDR connected to a laptop and from an ANTSDR locally connected to the Intel NUC.
Everything needed to get started is either already included in DragonOS Focal or is easily installed as shown in the video. A key part is the included SDR4space.lite application, however, a newer version with updated features is expected soon.
FutureSDR is an experimental open source SDR framework (similar to GNU Radio) that is being developed by Bastian Bloessl. The idea behind the framework is that it is implemented in Rust, which is a programming language that supports async (asynchronous) code. The end result to the user should be faster, more portable and lower latency digital signal processing (DSP) code. The framework is still in the early stages with there being very few DSP blocks available, but as per his blog new blocks are slowly being implemented by contributors.
Bastian has created a presentation introducing the framework. It will only be interesting to programmers, and DSP coders, but it shows the possible software engineering improvements that we could see applied to SDR DSP code in the future.
Features An experimental asynchronous SDR runtime for heterogeneous architectures that is:
Extensible: custom buffers (supporting accelerators like GPUs and FPGAs) and custom schedulers (optimized for your application).
Asynchronous: solving long-standing issues around IO, blocking, and timers.
Portable: Linux, Windows, Mac, WASM, Android, and prime support for embedded platforms through a REST API and web-based GUIs.
Fast: SDR go brrr!
Overview FutureSDR supports Blocks with synchronous or asynchronous implementations for stream-based or message-based data processing. Blocks can be combined to a Flowgraph and launched on a Runtime that is driven by a Scheduler. It includes:
Single and multi-threaded schedulers, including examples for application-specific implementations.
Portable GPU acceleration using the Vulkan API (supports Linux, Windows, Android, …).
User space DMA driver for Xilinx Zynq to interface FPGAs.
Over on YouTube Dr. Diep N. Nguyen has posted a video showing work done to create a Real Time spectrum database by his team at University of Technology Sydney. The project involves the use of multiple RTL-SDR dongles and Android mobile devices to monitor the spectrum and make it accessible to requestors in real time. They write:
In view of the escalating demand for higher mobile data (from IoT, industry 4.0 applications), there is a growing world-wide interest to improve the radio spectrum utilization. Effective management of the wireless spectrum requires knowledge of the available bandwidth at any given time and location, which necessitates expensive recording equipment and labour cost at various locations. A number of countries, including the USA, are opening up TV and radar bands for sharing with other applications. Google has taken the lead by opening its spectrum database for TV whitespaces. Our solution goes beyond the state-of-the-art Google spectrum database by providing the world’s first real-time radio spectrum database.
Radio Spectrum Database at UTS The UTS’s Global Big Data Technologies Centre team has developed advanced sensing capability to deliver a low-cost, yet more robust radio spectrum database. By leveraging big data science, edge computing power, crowdsourcing, and low-cost SDR (software defined radio) adaptors, a real-time snapshot of the wireless spectrum can be recorded on any Android device. The spectrum data is aggregated and visualize onto a web dashboard, allowing industry stakeholders and regulators to better facilitate dynamic radio spectrum monitoring and sharing.
Highlights:
• World’s first real-time spectrum database • Fast deployment and can cover a wide range of frequency • Provide spectrum on-demand to IoT, industry 4.0 applications • Rich datasets from millions of mobile users across various locations • 24/7 cost-effective and real-time radio spectrum monitoring system • Economical: $20 RTL-SDR adaptors and labor-free versus costly sensing equipment • Scalable: Cloud deployment allows infrastructure to be scaled as user base grows (millions of users) • Easy to use and install via Android Play Store • User-friendly interface with Google Map embedded system
In the past we've seen somewhat similar projects with Electrosense, and the 'BigWhoop' project.
