Notice: WXtoImg Website Down

Just a note that the website for the popular NOAA APT weather satellite decoding software WxtoImg is currently down, and may possibly never be revived. This software is commonly used with RTL-SDR dongles to download weather satellite images from the NOAA 15, 18 and 19 polar orbiting satellites.

It seems that the author of the software has not been maintaining the site and software for a while, although there was a brief update on the site back in 2017 when the professional version keys were released for free. But the keys reportedly no longer work. WXtoImg is closed source, so the code is not available either.

Some of the downloads are still available via archive.org, however it only seems to be the Windows and some of the Linux versions that were archived. Over on two Reddit threads [1] [2], some users are also collecting the last free versions and making them available for download again. If anyone has access to the last beta versions for ARM devices please upload them somewhere too.

Also if anyone happens to have the contact details of the author, or someone who knows the author please let us know as we'd like to ask for permission to mirror the files.

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GQRX and gr-osmosdr now with support for SpyServer

Thanks to the work of Lucas Teske, GQRX is now able to connect to SpyServer servers. SpyServer is the IQ streaming server software solution developed by the Airspy SDR developers. It can support Airspy and RTL-SDR devices, and can be used to access these SDRs remotely over a network connection. It is similar to rtl_tcp, but a lot more efficient in terms of network usage, meaning that it performs well over an internet connection. On a previous post we have a tutorial about setting up a SpyServer with an RTL-SDR.

The code modified by Lucas is the gr-osmosdr module, and Lucas' code can be downloaded from his GitHub at github.com/racerxdl/gr-osmosdr. It doesn't yet appear to have been merged into the official osmocom branch. The gr-osmosdr module is a generic block used to access various SDR hardware, so any software that utilizes it (such as GNU Radio) should be able to connect to a SpyServer connection too.

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Building an RF Direction Finding Robot with an RTL-SDR

Over on Hackaday.io, project logger Humpelstilzchen has been writing about his attempts to create an autonomous RF direction finding robot RC car with an RTL-SDR. The goal is to set up an ISM band transmitter as a beacon, and use the RTL-SDR on the robot as the receiver. It will then use direction finding techniques to drive towards the beacon. The robot is a 4WD RC toy car with some autonomous navigational features like GPS, ultrasonic, IMU and vision sensors.

In his latest project log Humpelstilzchen describes his first semi-successful attempt at getting RF direction finding working. In the experiment he uses a 433 MHz module to send out an FSK beacon. On the robot two antennas are used for the time difference of arrival/pseudo-doppler direction finding technique, and PIN diodes are used to rapidly switch between the antennas. A GNU Radio script running on a HummingBoard single board computer computes the TDOA/pseudo-doppler algorithm.

Psuedo-doppler direction finding works by rapidly switching between several antennas. The difference in the time that the signal arrives at each antenna can be used to calculate the transmitter's direction.

With the current set up he's been able to get the robot to distinguish if the beacon is closer to the left, or closer to the right, or equidistant. However, he notes that there are still problems with reflections of the beacon signal which can cause the robot to drive in the wrong direction.

This is still a work in progress and we look forward to his future results.

Humpelstilzchen's RF direction finding robot
Humpelstilzchen's RF direction finding robot
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Generating a WiFi Radio Heatmap with a Helical Antenna, Antenna Rotator and a HackRF

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.

WiFi Heatmap Building Scan Results
The Thought Emporiums' WiFi Heatmap Building Scan Results

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 Version 2: Wifi vision - Part 1

DIY Radio Telescope V2: Wifi Vision - Part 2
DIY Radio Telescope V2: Wifi Vision - Part 2

Building a Camera That Can See Wifi | Radio Telescope V2 - Part 3 SUCCESS!
Building a Camera That Can See Wifi | Radio Telescope V2 - Part 3 SUCCESS!

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Tutorial: Setting up a Low Cost QRP (FT8, JT9, WSPR etc) Monitoring Station with an RTL-SDR V3 and Raspberry Pi 3

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)
  • Internet connection
  • Band filter (optional but recommended)
  • HF antenna (this could be as simple as a long wire)

Examples of QRP Receivers with an RTL-SDR

Monitoring FT8, JT9, JT65 and WSPR simultaneously with an RTL-SDR V3 and Pi 3
Monitoring FT8, JT9, JT65 and WSPR simultaneously with an RTL-SDR V3 and Pi 3

RASPBERRY PI3 SDR Monitor 40m FT8/JT65/JT9 (RTL-SDR/LINRAD)
RASPBERRY PI3 SDR Monitor 40m FT8/JT65/JT9 (RTL-SDR/LINRAD)

Continue reading →

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The Artificial Intelligence Radio – Transceiver

Over on Crowd funding site Crowd Supply, a new SDR product is currently awaiting release of its crowd funding stage. The proposed product is called the AIR-T, which stands for Artificial Intelligence Radio - Transceiver. The basic idea behind the board is to combine a 2x2 MIMO SDR transceiver with a NVIDIA Jetson TX2 GPU that can be used to run artificial intelligence (AI) software fast.

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:

Wireless

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.

Satellite Communications

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.

Ground Communications

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.

Video/Image/Audio Recognition

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.

Pattern Recognition

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.

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Software Defined Radio Talks from the Friedrichshafen Ham Radio Convention

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
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
András Retzler, HA7ILM: Let's code a simple receiver in C

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Software Defined Radio for Engineers: Free University Level Text Book with PlutoSDR Examples

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.

The full book can be purchased as a Hardcover from Amazon, or downloaded freely online as a PDF.

If you're interested in a similar book, there is also the free DesktopSDR book which uses RTL-SDR dongles for the practical examples.

SDR For Engineers Book
SDR For Engineers Book
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