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.
Just a reminder than GNU Radio Conference 2021 (GRCON21) will be going ahead on Sept 20 - 24 with virtual and in-person events. It is free to register for virtual attendance and you will be able to view all talks live via streaming. If you wish to attend workshops virtually, the registration fee is $50. All links for YouTube live streaming can be found on the virtual attendance page as well. Be sure to use the YouTube "set reminder" feature to be notified when the streams begin.
GNU Radio Conference (GRCon) is the annual conference for the GNU Radio project and community, and has established itself as one of the premier industry events for Software Radio. It is a week-long conference that includes high-quality technical content and valuable networking opportunities. GRCon is a venue that highlights design, implementation, and theory that has been practically applied in a useful way. GRCon attendees come from a large variety of backgrounds, including industry, academia, government, and hobbyists.
The yearly GNU Radio Conference (GRCon) is a conference all about the development of GNU Radio and projects based on GNU Radio. GNU Radio is an open source digital signal processing (DSP) toolkit which is often used in cutting edge radio applications and research to implement decoders, demodulators and various other SDR algorithms.
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.
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.
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.
Daniel Estévez often posts on his blog about advanced SDR and radio experiments he's worked on. In a recent post he describes how he decoded telemetry from the Voyager 1 spacecraft using GNU Radio. As Voyager 1 is so far away, and the signal so weak, a rather large scale 100 meter dish is required to receive Voyager 1. So he uses publicly available recorded data received by the Green Bank Telescope in 2015.
Using GNU Radio he first converts the telescope's data file discarding most of the 187.5 MHz recorded bandwidth, then decimates the signal allowing the very weak carrier and data subcarriers to be seen in the resulting high resolution FFT plot. Daniel notes how most of the power is spent in the carrier, allowing ground stations to more easily detect the signal and at least measure doppler to determine the spacecrafts trajectory. The rest of the post explains how the carrier is tracked, how to correct for doppler and phase shifts, how to demodulate the data, apply error correction, and finally decode the data packet.
While not something we can easily listen to directly, it is amazing that we can all be NASA engineers right at home with GNU Radio and tutorials like this.
Voyager 1's Spectrum. Strong carrier in the middle, and two data subcarriers.
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.
About a month ago we posted about the Arinst Dreamkit, which was an unreleased Russian made portable receive only SDR with 16-bit ADC, 1 - 3100 MHz tuning range, up to 5 MHz instantaneous bandwidth, and very fast scanning capabilities.
Reader 'sunny' has written in and informed us that the Arinst Dreamkit is now released and available for sale on both eBay and Aliexpress. The pricing is $230 + shipping costs. Sunny notes that the manual is only in Russian, and currently it does not have any digital decoding capabilities, and no preselector on the input.
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.
RF WATCHER MICRO
The programs don't appear to be available to the public yet, but we will follow up with Manahiyo.
![[Volume warning] RTL-SDR×VR(Virtual Reality) with oculus quest2](https://www.rtl-sdr.com/wp-content/plugins/wp-youtube-lyte/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FLzDLyCjDgJU%2F0.jpg)
