Tagged: rtl-sdr

A Video Tutorial about Receiving HRPT Weather Satellite Images

Over on YouTube 'Tysonpower' has recently uploaded a very informative video and blog post showing how he is able to receive HRPT weather satellite images. Note that the video is in German, but English subtitles are provided.

Most readers of this blog are probably familiar with the more commonly received APT images that are broadcast by the NOAA satellites at 137 MHz, or perhaps the LRPT images also broadcast at 137 MHz by the Russian Meteor M2 satellite. HRPT signals are a little different and more difficult to receive as they are broadcast in the L-band at about 1.7 GHz. Receiving them requires a dish antenna (or high gain Yagi antenna), L-band dish feed, LNA and a high bandwidth SDR such as an Airspy Mini. The result is a high resolution and uncompressed image with several more color channels compared to APT and LRPT images.

In his video Tysonpower shows how he receives the signal with his 3D printed L-band feed, a 80cm offset dish antenna (or 1.2m dish antenna), two SPF5189Z based LNAs and an Airspy Mini. As L-band signals are fairly directional Tysonpower points the dish antenna manually at the satellite as it passes over. He notes that a mechanised rotator would work a lot better though. For software he uses the commercial software available directly from USA-Satcom.com.

[EN subs] HRPT - Erste Bilder! und mein Setup

An Example HRPT Image Received by Tysonpower.
An Example HRPT Image Received by Tysonpower.

FM2TXT: Automatically Perform Speech to Text on FM Signals

SourceForge user randaller has recently released a potentially useful Python program called FM2TXT. The FM2TXT program uses the Google speech recognition libraries and an RTL-SDR to listen to any broadcast FM station and automatically transcribe the speech into text. The code seems to be basically an interface for the Google speech recognition API, so is nothing fancy, but still may be of interest to some. Also at the moment it seems like it only works with broadcast FM (WFM), but as the code is open source and consists of a simple single Python file it shouldn't be too hard to adapt it for other NFM signals too. 

No word yet on the accuracy of the speech recognition or how well it works with poor reception. If you are interested there is also a Reddit thread discussing the software here. 

The Google Speech Recognition API
The Google Speech Recognition API

A Tutorial on using SDRAngel for DMR, D-Star and Fusion Reception with an RTL-SDR

At the end of last month we uploaded a post highlighting the SDRAngel software, which is a general purpose SDR program with some interesting features such as built in digital speech decoders for DMR, D-Star and Fusion. This avoids the need to pipe audio into a separate digital speech decoder program such as DSD+. SDRAngel also has transmit capabilities which makes it useful for SDRs such as the HackRF, PlutoSDR, LimeSDR etc.

Now over on YouTube and his blog K2GOG has uploaded a video tutorial about using SDRAngel. The tutorial starts with installing SDRAngel and explaining that you'll need a 64-bit system and OS to run it. He then goes on to show how to do FM reception and finally how to do digital speech decoding.

Deep Learning Neural Network Signal Identification Software for the RTL-SDR

Recently GitHub user randaller released a piece of software that utilizes the RTL-SDR and neural networks for RF signal identification. An artificial neural network is an machine learning technique that is based on approximate computational models of neurons in a brain. By training the neural network on various samples of signals it can learn them just like a human brain could. A neural network trained on signal classification can then be used by anyone to identify unknown signals. Randallers neural network software can learn either from raw IQ data, FFT processed samples, slightly demodulated data, or demodulated audio data. The tensorflow machine learning library is used as the base code, and the deep learning technique is used.

At the moment the software is only really proof of concept, and the currently trained model is only able to identify WFM, TV SECAM Carriers and TETRA. It should be possible to train the network further by providing your own samples too, but a good graphics card is required for this as the software makes use of GPU processing for training. The output of the software is a percentage which shows how confident the neural network is that it is identifying a signal correctly.

If you are interested, there is also a Reddit thread discussing this software here.

Artificial Neural Network being used to identify a WFM signal with an RTL-SDR
Artificial Neural Network being used to identify a WFM signal with an RTL-SDR

More Information on The Android RTL-SDR Direction Finding Implementation

Last week we posted about some interesting conference talk videos from GNU Radio Con 17. One of the videos was a talk by Sam Whiting who in conjunction with colleagues Dana Sorensen and Todd Moon from Utah State University have created an Android app that uses two coherent RTL-SDR dongles for direction finding. A coherent RTL-SDR can be created simply by removing the clock on one RTL-SDR and connecting the clock from another, so that they both share the same clock. The V3 RTL-SDR has a clock selector header which can be used to facilitate this as well.

Over on his YouTube account Sam Whiting has uploaded two videos showing the app in action. The backend GNU Radio code for direction analysis is available on GitHub, but unfortunately the Android code/apk is not available to the public as the code is owned by the funders of the project.

In the videos the app shows two arrows, one of which points towards the source of a transmission at a frequency that is being monitored. The second arrow is simply there due to the direction ambiguity produced by the methods used.

The GRCon17 presentation video can be found here, and the slides here.

Using a Slinky as a Cheap Antenna for the 80m Band

A slinky is a fun little toy that is essentially a long and loose spring. You can perform tricks with them, but the most iconic use is making them walk down stairs all by themselves. Over on Hackaday we've seen a tutorial that shows how to use a slinky as a good antenna for the 80m (3.5 MHz) band. Using a slinky as an antenna is nothing new to hams, but the original post on imgur shows some pretty clear photos and instructions on how to construct one.

The text written by the original poster on imgur notes that he uses this antenna very successfully with his RTL-SDR in direct sampling mode and this even outperforms his regular shortwave radio. He notes that slinkies aren't weather proof, so some sort of weather proofing spray coating or oil might be useful for a permanent set up.

If you are interested apart from the discussion on Hackaday there is also a comments thread on Reddit where the original poster discusses what he purchased.

Slink Antenna for 80m
Slinky Antenna for 80m

NOAA using the SDRplay RSP2 and RTL-SDR for Receiving Weather Balloon Data

NOAA RSP2 setup for Receiving Radiosonde Data
NOAA RSP2 setup for Receiving Radiosonde Data

Over on the SDRplay forums there has been a post by a NOAA engineer showing how they are using SDRplay RSP2 units in the field for tracking their radiosonde weather balloons. A radiosonde is a small sensor package and transmitter that is carried high into the atmosphere by a weather balloon. It gathers weather data whilst transmitting the data live back down to a base stations. You can get data such as temperature, pressure, humidity, altitude and GPS location.

Bobasaurus' coworker launching a weather balloon.
Bobasaurus' coworker launching a weather balloon.

The NOAA engineer on the forum (handle 'bobasaurus') wrote SkySonde, which is the software used by NOAA to decode and plot data from the radiosondes. SkySonde is freely available for public download on the NOAA website. A PDF file showing how to use the SkySonde software with an RSP2 or RTL-SDR can be found here, and the full SkySonde manual is available here. The software consists of a client and server, with the server connecting to the RSP2 or RTL-SDR, and then sending data to the client. Both server and client can run on the same PC.

The hardware setup consists of an RSP2 (can be interchanged with an RTL-SDR), an Uputronics Radiosonde Filtered preamp and a Yagi antenna. Presumably a Yagi and LNA is not completely required, although the receivable range will be less. The RSP2 bias tee is used to power the preamp, and on a V3 RTL-SDR the bias tee should also work.

NOAA appears to use the iMet brand of radiosondes which transmit a Bell 202 signal. Bobasaurus writes that they transmit in the 401-405 MHz range. This video shows an example of such a signal. If you are in the US near an area that launches these iMet weather balloons you should be able to receive them. An alternative piece of software that supports iMet radiosondes is RS. For other radiosondes we have a tutorial that uses SondeMonitor available here.

SkySonde Radiosonde Software
SkySonde Radiosonde Software

GR-Con17 Talks: GPS Beamforming with RTL-SDRs, Direction Finding with RTL-SDRs on Android and much more

GRCon17 is the yearly convention all about GNU Radio and the talks are generally all about technical cutting edge developments in the software area of the SDR world. If you didn't already know, GNU Radio is an open source tool that makes implementing digital signal processing code significantly easier by providing a framework and several ready to use DSP blocks. It is an advanced tool used a lot in industry and research, but the visual nature of the blocks means that the basics can be easily learned in a few days. See Micheal Ossmans video tutorials for an excellent introduction.

This year at GRCon17 there were multiple interesting talks, and over the last few days videos of them have been released on YouTube. Slides for each presentation are also available in the YouTube description boxes. The full list of presentations can also be found on the Technical Processing page at GNURadio. A selection of our favorites videos are presented below, with several talks utilizing low cost RTL-SDRs as the core radio in the research.

GPS Beamforming with Low-Cost RTL-SDRs - Wil Myrick

In this talk Wil Myrick discusses how he's been using low cost RTL-SDR dongles to perform beamforming experiments with GPS signals.

GRCon17 - GPS Beamforming with Low-Cost RTL-SDRs - Wil Myrick

Real-Time Direction Finding Using Two Antennas on an Android Phone - Sam Whiting

In this talk Sam Whiting shows how he used two coherent RTL-SDR dongles running on on an Android phone for direction finding. At the end of the video he demonstrates his results.

GRCon17 - Real-Time Direction Finding Using Two Antennas on an Android Phone - Sam Whiting

Hacking the Wireless World 4.0 - Balint Seeber

In this video Balint Seeber continues with his popular Hacking the Wireless World series of talks and this time talks about FMCW & Passive Radar and FPV decoding with SDRs.

GRCon17 - Hacking the Wireless World 4.0 - Balint Seeber