Over on YouTube The Thought Emporium channel has been working on creating a "WiFi Camera" over the past few weeks. The idea is to essentially create a small radio telescope that can "see" WiFi signals, by generating a heatmap of WiFi signal strength. This is done with a directional helical 2.4 GHz antenna and motorized rotator that incrementally steps the antenna through various angles. After each movement step a HackRF and Python script is used to measure WiFi signal strength for a brief moment, and then the rotator moves onto the next angle. The helical antenna and rotator that they created are made out of PVC pipe plastic and wood, and are designed to be built by anyone with basic workshop tools like a bandsaw.
The final results show that they've been able to successfully generate heatmaps that can be overlaid on top of a photo. The areas that show higher signal strength correlate with areas on the photo where WiFi routers are placed, so the results appear to be accurate. In the future they hope to expand this idea and create a skyward pointing radio telescope for generating images of the galactic hydrogen line, and of satellites.
The videos are split into three parts. The first two videos show the build process of the antennas and rotator, whilst the third video shows the final results.
DIY Radio Telescope Version 2: Wifi vision - Part 1
DIY Radio Telescope V2: Wifi Vision - Part 2
Building a Camera That Can See Wifi | Radio Telescope V2 - Part 3 SUCCESS!
QRP is amateur radio slang for 'low transmit power'. QRP digital modes such as FT8, JT9, JT65 and WSPR are modes designed to be transmit and received across the world on low transmit powers (although not everyone uses only low power). The special design of these modes allows even weak signals to be decodable by the receiving software. Released in 2017, FT8 has shown itself to now be the most popular mode by far with JT9 and JT65 taking a backseat. WSPR is also not as active as FT8, although WSPR is more of a beacon mode rather one used for making contacts.
Apart from being used by hams to make contacts, these weak signal modes are also valuable indicators of the current HF propagation conditions. Each packet contains information on the location of the transmitter, so you can see where and how far away the packet you've received comes from. You also don't need to be a ham to set up a monitoring station. As an SWL (shortwave listener), it can be quite interesting to simply see how far away you can receive from, and how many countries in the world you can 'collect' signals from.
This tutorial is inspired by dg0opk's videos and blog post on monitoring QRP with single board computers. We'll show you how to set up a super cheap QRP monitoring station using an RTL-SDR V3 and a Raspberry Pi 3. The total cost should be about US $56 ($21 for the RTL-SDR V3, and $35 for the Pi 3).
With this setup you'll be able to continuously monitor multiple modes within the same band simultaneously (e.g. monitor 20 meter FT8, JT65+JT9 and WSPR all on one dongle at the same time). The method for creating multiple channels in Linux may also be useful for other applications. If you happen to have an upconverter or a better SDR to dedicate to monitoring such as an SDRplay or an Airspy HF+, then this can substitute for the RTL-SDR V3 as well. The parts you'll need are as follows:
RTL-SDR V3 (or upconverter, or other HF & Linux capable SDR)
Raspberry Pi 3 (or other SBC with similar performance)
Band filter (optional but recommended)
HF antenna (this could be as simple as a long wire)
The SDR transceiver chip used is a Analog Devices 9371. This is a high end chip that can be found on high end SDR hardware like USRPs. If you're interested we had a post about decapping the AD9361 recently, which is a similar chip. It provides 2x2 MIMO channels, with up to 100 MHz RX bandwidth and 250 MHz TX bandwidth. The NVDIA Jetson TX2 is a GPU 'supercomputer' module specifically designed for AI processing. Many AI/machine learning algorithms, such as neural networks and deep learning run significantly faster on GPU type processors when compared to more general CPU's.
These are not cheap chips with the AD9371 coming in at over US$250 each, and the Jetson TX2 coming in at US $467. Although we don't know what sort of bulk discounts the AIR-T manufactures could get. But it will be certain that the AIR-T will not be for the budget minded.
The board is still awaiting release of it's crowdfunding round, and you can sign up to be notified of when the project launches on their Crowd Supply page.
The melding of AI and the RF spectrum will be common in the future, and a development board like this is one of the first steps. Some of the interesting use cases that they present are pasted below:
From Wi-Fi to OpenBTS, use deep learning to maximize these applications. By pairing a GPU directly with an RF front-end it eliminates the need of having to purchase an additional computer or server for processing. Just power the AIR-T on and plug in a keyboard, mouse, and monitor and get started. Use GNURadio blocks to quickly develop and deploy your current or new wireless system. For those who need more control, talk directly with the drivers using Python or C+. And for those superusers out there, the AIR-T is an open-platform, so you can program the FPGA and GPU directly.
Communicating past Pluto is hard. With the power of a single-board SDR with an embedded GPU, the AIR-T can certainly prove out concepts before you launch them into space. Reduce development time and costs by adding deep learning to your satellite communication system.
There is an endless number of terrestrial communication systems with more being developed every day. As the spectral density becomes more congested, AI will be needed to maximize these resources. The AIR-T is well-positioned to easily and quickly help you prototype and deploy your wireless system.
The AIR-T allows you to demodulate a signal and apply deep learning to the image, video, or audio data in one integrated platform. For example, directly receiving a signal that contains audio and peforming speech recognition previously required multiple devices. The AIR-T integrates this into one easy to use package. Whatever your application is, from speech recognition to digital signal processing, the integrated NVIDIA GPU will jump start your applications.
For many communications and radar applications once the signal is collected it must be sent to an off-board computer for additional processing and storage. This consumes valuable time. The AIR-T eliminates this. From its inception, it was designed to process signals in real-time and eliminate unnecessary latency.
Several new software defined radio talks have been released on YouTube this week from the big European 2018 Friedrichshafen Ham Radio Convention which just finished this month. The full list of 14 new videos can be found on the Software Defined Radio Academy YouTube channel. Below are two of our favorites:
The OVI40 / UHSDR Project, Developing An Open Standalone SDR
OVI40 is an Open Source standalone homewbrew SDR TRX project (VLF to 2m), developed with the aim of being modular and future-proof. The talk describes the hardware and the UHSDR software including a discussion on the evolution from the "single-system" software used for the well-known mcHF (initially written by Chris, M0NKA and Clint KA7OEI) to the multi-SDR approach in the UHSDR software project.
DF8OE, DB4PLE, DL2FW, DD4WH: The OVI40 / UHSDR Project - Part 1 and 2
András Retzler, HA7ILM: Let's code a simple receiver in C
For using SDR in amateur radio applications, it is easier to use existing receiver software, or create GNU Radio flowgraphs with pre-build blocks. On the contrary, in the do-it-yourself spirit of amateur radio, this talk will guide you through the steps of implementing a simple AM/FM/SSB receiver from scratch, in plan old C, in order to get a deeper understanding of what happens actually under the hood in popular SDR software. The talk builds on the author's learning experience of creating the open source CSDR command line tool, which is used for DSP in the OpneWebRX web based SDR receiver.
András Retzler, HA7ILM: Let's code a simple receiver in C
Analog Devices has recently released a new text book for free called "Software-Defined Radio for Engineers, 2018". This is an advanced university level text book that covers communication systems theory as well as software defined radio theory and practice. The book uses the PlutoSDR as reference hardware and for practical examples. The PlutoSDR is Analog Devices $150 RX/TX capable SDR that was released about a year ago.
The objective of this book is to provide a hands-on learning experience using Software Defined Radio for engineering students and industry practitioners who are interested in mastering the design, implementation, and experimentation of communication systems. This book provides a fresh perspective on understanding and creating new communication systems from scratch. Communication system engineers need to understand the impact of the hardware on the performance of the communication algorithms being used and how well the overall system operates in terms of successfully recovering the intercepted signal.
This book is written for both industry practitioners who are seeking to enhance their skill set by learning about the design and implementation of communication systems using SDR technology, as well as both undergraduate and graduate students who would like to learn about and master communication systems technology in order to become the next generation of industry practitioners and academic researchers. The book contains theoretical explanations about the various elements forming a communication system, practical hands-on examples and lessons that help synthesize these concepts, and a wealth of important facts and details to take into consideration when building a real-world communication system.
The companion site for the book which contains links to complimentary online lectures, slides, and example MATLAB code can be found at https://sdrforengineers.github.io. MATLAB is a very powerful programming language and toolset used by scientists and engineers. MATLAB is not a cheap tool, but there is a home user licence available for a more reasonable price. To do some of the exercises in the book you'll probably at least require the core MATLAB plus the Communications System Toolkit which is an extra add on.
Back in January of this year we posted about PhD student Lucas Riobó's work that about about using an RTL-SDR to create a low cost optical "high-speed real-time heterodyne interferometer". In that work he used an RTL-SDR as a data acquisition tool for an optoelectronic front end sensor (opto = visual light). This allowed him to translate optical data into an RF signal, which could be received by the RTL-SDR, and then easily processed in a PC.
In this work, a general architecture for the implementation of software-defined optoelectronic systems (SDOs) is described. This concept harnesses the flexibility of software-defined hardware (SDH) to implement optoelectronic systems which can be configured to adapt to multiple high speed optical engineering applications. As an application example, a software-defined optical interferometer (SDOI) using the LimeSDR platform is built. The system is tested by performing high speed optical detection of laser-induced photoacoustic signals in a concentrated dye solution. Using software modifications only, conventional single carrier and also multicarrier heterodyne techniques with space and frequency diversity are performed.
A main difference with the other article described in this post, is that we could also use the transmission path of the LimeSDR to perform many modulation waveforms of the electromagnetic fields which will interfere, to provide a noticeable performance improvement in single-shot interferometric measurements.
Steve Andrew has just released an alpha version of a Windows Spectrum Analyzer app for SDRplay SDRs that he's been working on. The app is currently still in alpha, meaning that all the features are not yet implemented. In particular, scans larger than the SDRplay's maximum bandwidth of 10 MHz are not ready yet. In the future the app will be able to scan swath's of bandwidth up to 2 GHz wide, similar to what SpectrumSpy for the Airspy and rtl_power for the RTL-SDR does.
We are pleased to announce the availability of the first cut of Spectrum Analyser software developed by Steve Andrew specifically for the RSP line of products. Please note that this is first alpha software and so it is still very much in development and some features are still to be added. Currently supported are:
RSP1 RSP2/RSP2pro RSP1A
This first alpha release gives a good idea as to the look and feel for the software. The main functional limitation is that sweeps of greater than 10 MHz are not currently supported. Steve is currently re-working the algorithms for providing wider sweeps than 10 MHz to improve sweep time and remove the issue of the DC spike in ZIF mode, so please bear with him.
We recommend using the software with AGC turned off and use manual control of the gain for better display stability.
Please use this forum thread to post any issues. Read the issues already raised and only post if the issue you have found hasn’t been raised. This will help Steve in his development.
Further development information can be found on the forum.
Over on YouTube Corrosive has published a video of him browsing through the UHF Satcom band with a remote Airspy SDR being streamed via SpyServer. The UHF-Satcom band is anywhere between 243 - 270 MHz and contains fairly strong signals from many several US satellites that can be received with a simple antenna. Some of the satellites are simple repeaters without security, and pirates from Mexico and South America often hijack the satellite for their own personal use. So it can be quite interesting to look for pirate conversations and sometimes SSTV images. Reception of these satellites is generally available in Canada, US, Mexico, South America, Europe and Africa.
UHF Satcom Transponders Close Up on the Airspy SDR