Tagged: rtl-sdr

TechMinds: Testing SDR++ The Bloat Free SDR Software

Over on YouTube TechMinds has recently released a video where he overview SDR++, dubbed as the "bloat free SDR software". We've been following the development of SDR++ for a while, and recently posted about the release of version V1.0.0. SDR++ is an open source, cross platform, C++ based GUI general receiver program for various SDRs including the RTL-SDR. In another recent post we also saw a video review from Sarah at SignalsEverywhere.

The the video TechMinds gives an overview of the SDR++ features and GUI, and also shows DSD+ and WSJT-X running together with it. He notes that SDR++ lives up to it's expectations and lives up to it's bloat free tagline.

SDR++ Multi Platform SDR Application

SDR Talks from the SDRMakerspace Online Presentation

Thank you to Robert for letting us know about these videos from the "ESA ARTES SDR MakerSpace Presentations" from September 6-8, 2021 which are now available on YouTube. 

Libre Space Foundation ( Greece) and the Institute of Reconfigurable & Embedded Digital Systems(REDS) of the Haute Ecole d’Ingénierie et de Gestion du Canton de Vaud – HEIG-VD (Switzerland) have been implementing a number of smaller projects as part of an Software Defined Radio MakerSpace of the European Space Agency.

This activity is part of the ARTES programme of ESA that supports innovation in satellite communications.

The findings were presented in three 2-hour slots in the afternoon at 15:00 CEST (for which you are requested to register separately) on Mon 6, Tue 7 and Wed 8 September 2021.

  • Monday 6 Sep was focused on the evaluation of various SDR boards and FPGA tools chains. High-rate direct sampling by SDR’s and SDR on Android will also be presented.
  • Tuesday 7 Sep was dedicated to building blocks that have been implemented as open source developments for Gnuradio, such as gr-leo, gr-ccsds, gr-soapy etc.
  • Wednesday 8 Sep was mainly about the combination of SDR and AI/ML to do signal detection and classification. In addition, an SDR testbed and spectrum monitoring will be presented.

The talks cover various SDR topics related to satellite observing. Some talks we were interested in are highlighted below, but the full list can be found on the SDRMakerspace website, or the SDRMakerspace playlist on the Libre Space Foundation YouTube channel.

SDRMakerspace - SDR on mobile

Decoding the RF Output of a VCR with an RTL-SDR

Over on YouTube use Scelly has uploaded a video showing how he has used an RTL-SDR dongle and the TVSharp SDR# plugin to decode video from the RF output of an old VCR (videocassette recorder). VCR players were designed to output the same PAL or NTSC signal that old analog TV transmissions used, and the RF output of the VCR was connected directly to the TV's antenna input.

The TVSharp plugin for SDR# can be used to decode these signals, however as the bandwidth of PAL/NTSC signals is much larger than the 2.4 MHz provided by the RTL-SDR, only a black and white image can be received. Scelly writes:

RF Output from VCR connected directly to input of my RTL-SDR. The RF output is tuned to channel 22 (487.25 MHz), and as the signal is so wide, my RTL-SDR can only display the luminance data (black and white video) and audio, although not at the same time. If I had two RTL-SDRs or an SDR with a larger bandwidth, I could have both audio and video playing at the same time.

The video playing is "The Prince of Egypt" on VHS Video Cassette.

Decoding RF Output of a VCR with RTL-SDR Dongle

Video on Using RF Filters with an RTL-SDR

Over on YouTube channel TheSmokinApe has uploaded a video about using RF filters with an RTL-SDR. In the video he first explains why FM bandstop and AM high pass filters might be required when using a software defined radio in order to avoid overloading the SDR with very strong signals. He goes on to test and review our RTL-SDR Blog FM Bandstop and AM Highpass filters, by testing them on a spectrum analyzer.

RTL-SDR RF Filters

Near Field Localization with Machine Learning and 7 Coherent RTL-SDRs

Thanks to Laakso Mikko and Risto Wichman researchers at the Department of Signal Processing and Acoustics in Aalto University, Finland for submitting news that their recent paper titled "Near-field localization using machine learning: an empirical study" is available on IEEE Xplore. (To access the paper you need an IEEE subscription, but we see no harm in letting individuals know that they can search for the DOI on sci-hub to get it for free).

The work described in the paper uses 7 RTL-SDR dongles with their clocks connected together. Combined with noise source calibration, this results in a coherent SDR. They then train a Deep Neural Network to perform near field localization using an antenna array. If you are interested, we have out own 5-channel coherent SDR called "KrakenSDR" which will soon be released for crowd funding. The abstract reads:

Estimation methods for passive near-field localization have been studied to an appreciable extent in signal processing research. Such localization methods find use in various applications, for instance in medical imaging. However, methods based on the standard near-field signal model can be inaccurate in real-world applications, due to deficiencies of the model itself and hardware imperfections. It is expected that deep neural network (DNN) based estimation methods trained on the nonideal sensor array signals could outperform the model-driven alternatives. In this work, a DNN based estimator is trained and validated on a set of real world measured data. The series of measurements was conducted with an inexpensive custom built multichannel software-defined radio (SDR) receiver, which makes the nonidealities more prominent. The results show that a DNN based localization estimator clearly outperforms the compared model-driven method.

The paper notes that the code used in the experiments is open source and available on GitHub.

If you're interested, we also posted about Laakso's previous work on beamforming with a phase coherent 21-channel RTL-SDR array back in February.

Examples of MUSIC pseudospectra. The units are [m] for range r on the vertical axis and degrees for θ on the horizontal axis. Red crosses mark the true location and black circles the NFLOPnet estimated location.

Installing Remote SDR V2 on a Raspberry Pi 4B

Remote SDR V2 is software that allows you to easily remotely access either a PlutoSDR, HackRF or RTL-SDR software defined radio. It was originally designed to be used with the amateur radio QO-100 satellite, but version 2.0 includes multiple demodulation modes, NBFM/SSB transmission capability, CTCSS and DTMF encoders, modulation compression and a programmable frequency shift for relays.

Over on the programmers blog, F1ATB has put out a new post showing how to install Remote SDR V2 on a Raspberry Pi 4B. The installation has been made simple thanks for a ready to use SD card image.

If you're interested in an overview of Remote SDR V2, we have posted previously about a Tech Minds review of the software.

Remote SDR V2 with a PlutoSDR

Viewing the RF Spectrum in Virtual Reality + Augmented Reality EMC Probe

Thank you to Manahiyo for submitting his video which shows his software that allows the RF spectrum to be viewed in virtual reality, using a VR headset and an RTL-SDR. In his setup he currently uses a Oculus Quest 2 VR headset, but it should work with others too. The VR screen allows you to have multiple graphs set up, as well as allowing you to explore a 3D spectrograph from all angles by moving it around via the pointer, or by moving your head. 

[Volume warning] RTL-SDR×VR(Virtual Reality) with oculus quest2

Manahiyo also has another new VR video on his channel where he uses his RF Watcher software. RF Watcher is his software that allows augmented reality and RF power measurements from an RTL-SDR to be combined. His video demonstrates him using an RTL-SDR and EMC probe, together with RF watcher. As the EMC probe is moved over an RF 'hot spot' on a PCB, red dots are drawn around it in augmented reality.

The programs don't appear to be available to the public yet, but we will follow up with Manahiyo.

Receiving the ‘Hidden’ Broadcast FM SCA Audio Subcarrier with an RTL-SDR and SDR#

Broadcast FM channels can often contain additional subcarriers hidden within the bandwidth. A common subcarrier is Radio Data System (RDS), and this is what provides song and radio station text information to your radio.

Another less commonly seen subcarrier is the Subsidiary communications authority (SCA), which is a separate audio channel hidden within the broadcast FM signal. SCA is typically used for niche radio programs, elevator music, music for doctors offices, and niche services such as reading for the visually impaired. In the past you needed a special hardware SCA radio to receive these channels, however receiving these channels with an SDR is relatively simple. Not all broadcast FM stations will have an SCA service, but the video shown below explains how to find one.

Over on YouTube channel Double A has uploaded a video showing how to decode these SCA subcarriers using an RTL-SDR, two SDR# instances and the MPX Output plugin. The idea to to use a virtual audio cable to pipe the FM Multiplex (MPX) audio output from one instance of SDR# to another. In the second SDR# instance you can then directly tune into the SCA channel. In his video he also explores the FM MPX spectrum, showing the different components, and also how to install and use RDS Spy for decoding RDS.

Tuning an FM Audio Subcarrier (SCA) & Decoding RDS Data with RTL-SDR USB