Tagged: rtl2832

KrakenSDR Update: New Prototypes, Software Updates, Campaign to Release Soon

KrakenSDR is our 5-tuner coherent software defined radio based on RTL-SDR. It is the successor to the KerberosSDR and will be crowdfunded on Crowd Supply with the campaign due to begin soon. Please sign up to the KrakenSDR Crowd Supply mailing list to be notified as soon as the campaign begins, and to check out our previous videos demonstrating the unit in action.

With a 5-channel phase coherent RTL-SDR interesting applications like radio direction finding (RDF), passive radar and beam forming become possible. It can also be used as five separate RTL-SDRs for multichannel monitoring.

KrakenSDR Updates

Like many other projects we have been severely delayed by COVID work restrictions and the effects it's having on the supply chain, and I'd like to thank everyone who is keen to get a hold of a KrakenSDR for their patience. But the ball is rolling faster now and we have finally received our latest KrakenSDR prototypes! Testing has been ongoing for the last few days, and apart from a few minor issues everything is working brilliantly. At this stage we are confident in the design and are making plans to begin the crowdfunding campaign soon.

The latest KrakenSDR Prototype PCB running on a Pi 4.

Supply Chain Constraints

The first batch will unfortunately be limited to 1000 units maximum due to supply constraints and we expect this first batch to be ready 2-3 months after the campaign finishes. So if you are after a unit ASAP, please ensure you are on the CrowdSupply mailing list as we fully expect demand for the first batch to outstrip the supply.

But if you are willing to wait, batch 2 will be still be available at the campaign special price. we will have a second batch available for early preorder at a discount (sorry due to higher than expected shipping and skyrocketing component prices we can't discount the second batch at the moment). Please keep in mind that the second batch will be at least 6 months away due to the long supply chain resulting from the pandemic.

Next Steps

The next stages in hardware development will involve finalizing our custom milled aluminum enclosure, testing one last prototype, and beginning mass manufacturing when the crowd funding campaign is over.

Work on the software is ongoing, but the beta version of our new DAQ firmware and direction finding DSP software layer is stable and already available on the krakensdr GitHub at https://github.com/krakenrf. Everything resides in the development branches and there is full documentation on the code structure available in the Documentation folder. This code can also be used on the KerberosSDR by editing the configuration files to specify 4 receivers instead of 5.

By the time the units ship out we will have a ready to use SD card image for the Raspberry Pi 4 and a quickstart guide available.

KrakenSDR DAQ and DOA DSP Web Interface

Android App

We have also been working at improving the Android direction finding companion app. This app was made during the KerberosSDR release a couple of years ago, and is used to plot and log the direction finding bearings being generated by the Kerberos/KrakenSDR unit, combining it against the GPS and movement data generated by the Android phone. This Android phone + KrakenSDR combination results in a powerful multipath resistant radio direction finding tool, and once enough data has been collected (usually after a few minutes of driving) it is able to determine where the most likely transmitter location is.

The upgraded app makes use of the full 360 degrees of direction of arrival and multipath data that is generated by the KrakenSDR, resulting in a more accurate determination of the transmitter location, and a better understanding of the uncertainties. It also allows users to visualize multipath. There are also various bug fixes and improvements made overall. We are planning to transition this app into a paid app, but all KrakenSDR backers will receive a license for free and the older KerberosSDR app will remain free.

KrakenSDR Android App Improvements

KrakenSDR Antennas

To work as a radio direction finder, KrakenSDR needs five antennas. If you plan to use them in a circular array, they need to be omnidirectional antennas such as whips or dipoles. So to go along with the KrakenSDR we will be selling an optional set of five magnetic whip antennas which can be mounted on for example, the roof of a car. (Please note the magwhips shown in the photo may differ slightly from the final ones sold).

KrakenSDR Magnetic Whips on a Car Roof

We have also been working with Arrow Antennas in the USA, who are producing a KrakenSDR 5-element dipole array antenna which is great for use in fixed sites (for example on the roof of a house). The antenna will be sold by Arrow antennas (not by us), and the future link (not active yet) will be http://www.arrowantennas.com/arrowii/kraken.html. We expect them to generate this page within the next few days. This antenna has been used in all our fixed site experiments as you can see in some of the YouTube videos, and works very well. (The image below show a prototype, we're told the final version may look slightly different.)

Arrow Antenna 5-element antenna array for the KrakenSDR

Future Work

DAQ & Direction of Arrival (DOA / Radio Direction Finding) :
Work on the DAQ and DSP software is coming along well and this is mostly complete and runs stable on a Raspberry Pi 4. There are just now bug fixes and minor features being added. Intermittent 'bursty' signal handing is already working, but we are working on improving it's sensitivity to weak bursty narrowband CW signals which can still be problematic to detect. The Android app is also currently being field tested.

Passive Radar:
Work on new passive radar software is also ongoing and we expect to have something ready for experimentation and with quickstart guides before shipping. At the moment it is also still possible to use the older KerberosSDR software for passive radar, but we believe the new DAQ core software will run things much smoother. The goal for the new software is to not only plot a range-doppler map, but to combine it with direction finding and be able to plot radar detections on a map. This feature may require operation on a device faster than the Raspberry Pi 4, such as GPU based device like a NVIDIA Jetson.

Beam Forming, Interferometry:
One application we think the KrakenSDR would be great with is amateur radio astronomy via interferometry. The ability to combine multiple small hydrogen line dishes spread out over several meters of area should result in much greater radio imaging resolution, without needing to deal with a single huge dish. It may also allow for electrically steering a beam without needing to rotate the dishes.

Advanced Direction Finding + Advanced Log Management:
At the moment networked direction finding (direction finding via multiple fixed or mobile sites spread out around a city or area) is possible via the third party RDF Mapper software, but we aim to create our own advanced platform in the near future. The goal is to have software that will automatically log and alert when a signal of interest appears. For some examples we can see this being used to help coastguard locate distressed marine pleasurecraft that typically do not have AIS via their VHF radios, locate emergency beacons, for animal/wildlife/asset tracking, and monitoring for illegal/interference transmissions.

At this stage the core DAQ+DSP software will also be updated to support monitoring multiple simultaneous channels within the available 2.56 MHz bandwidth, and with a scanning and beacon ID detection feature.

Research into field applications:
One example we hope to test is the operation of KrakenSDR on a drone. With great line of sight from up in the sky, localizing a transmitter should be fast. Another example could be actually visualizing signals like light via augmented reality.

Some of our previous KerberosSDR and KrakenSDR posts might also be of interest.

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. 

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.