Thank you to Samual Yanz (N7FNV) for submitting a guide that he's created about tracking and decoding NOAA weather satellites. The guide can be downloaded from this link as a PDF.
Currently there are three operational polar orbiting NOAA weather satellites that transmit image data in the APT format at 137 MHz. When one of these satellites pass overhead, it is possible to use an RTL-SDR with appropriate satellite antenna and software to receive the satellite weather images they transmit.
Samual's guide focuses on the software and shows how to setup Virtual Audio Cable for piping audio between programs, SDR# for receiving the signal, Orbitron for tracking the satellite and WXtoIMG for decoding the image.
Thank you to Sasha Engelmann for letting us know about the release of the Open-Weather community's web browser based NOAA APT decoder. The decoder allows for easy NOAA satellite decoding by allowing you to upload a wav file recording of a NOAA satellite pass, and it will decode it into an image within the browser.
The project emerged from a desire to understand the process of decoding APT audio recordings into NOAA satellite images, and a need for an accessible browser-based decoder for new practitioners during open-weather DIY Satellite Ground Station workshops.
While we were inspired by Thatcher's APT 3000, we felt accessibility, documentation and features could be expanded and improved. open-weather apt allows you to select an audio file on your computer, choose a demodulation method, add histogram equalisation and download images. The website does not store your personal data, including your location or any files you upload.
Over on the usradioguy.com blog, Carl Reinemann has highlighted a very impressive remote off-grid radio satellite image receiver setup by Manuel Lausmann (DO3MLA). The setup consists of two Raspberry Pi's, two RTL-SDRs and a QFH satellite antenna connected to an antenna splitter and bias tee. It is able to receive APT and LRPT images from NOAA and Meteor satellites which transmit at 137 MHz. The received images are then uploaded to the internet via a mobile LTE router.
The system is located a remote part of Northern Norway and is powered by a dual solar and wind turbine system with battery storage. Being so remote with little interference, the system is able to receive very clean images, and with the location being so Northern, it can even glimpse the north pole.
Manuel has uploaded a YouTube video where he shows each part of the system. It is in narrated in German, however the YouTube caption auto translate feature can be used.
He notes that in the future he hopes to install a web SDR like KiwiSDR on the site too.
Researchers from Carnegie Mellon University have recently presented a paper detailing how they combined noisy signals from multiple passes of low earth orbit (LEO) satellites NOAA 15, NOAA 18 and NOAA 19 in order to create a higher quality image. For a receiver they used a low cost RTL-SDR Blog V3 mounted indoors with a whip antenna.
In a normal setup, weather satellite images from NOAA LEO weather satellites can be received with an RTL-SDR, computing device and an appropriate outdoor mounted antenna that has a good view of the sky. If the antenna is not suited for satellite reception, and/or is mounted indoors, at best only poor quality very noisy images can be received.
The researchers demonstrate that it is possible to combine noisy images received over time, and from different satellites in order to generate a higher quality image. The challenge is that the different satellites and different receiving times will all produce different images, because the satellites will be at a different location in the sky each pass. They note that simply transforming the images in the image domain would not work very well for highly noisy images, so instead they have devised a method to transform the images in the RF domain. The RF signals are then coherently combined before being demodulated into an image.
The results show that 10 noisy satellite images from the indoor system are comparable to one from a comparison outdoor system. However, they note some limitations in that the system assumes unchanging cloud cover during passes. In the future they hope to extend the system to cover other modulation schemes used by other low earth orbit satellites in order to increase the number of usable satellites.
Selfiestick: Combining noisy images from multiple NOAA satellites received by an indoor RTL-SDR system.
In December of last year we posted about a video demonstrating the many features that the SDRAngel software comes standard with. Recently they've added a new feature which are 3D maps that can be used to visualize signal data.
In the latest video demonstration they show these 3D maps projecting NOAA weather satellite images onto a 3D globe and at the same time tracking the NOAA satellites over the globe as it produces imagery. They also show the software visualizing a 3D model of aircraft on the globe, using live ADS-B data to show aircraft maneuvers when taking off, cruising and landing. With multiple SDRs they also show how the visualization can be combined with air traffic voice. Finally they also show marine vessels being visualized via live AIS data. There appear to be a wide range of vessel 3D models implemented.
SDRAngel is a general purpose software defined radio program that is compatible with most SDRs including the RTL-SDR. We've posted about it several times before on the blog, however we did not realize how much progress has occurred with developing various built in plugins and decoders for it.
Thanks to Jon for writing in and sharing with us a demonstration video that the SDRAngel team have released on their YouTube channel. From the video we can see that SDRAngel now comes stock with a whole host of built in decoders and apps for various radio applications making it close to an all-in-one SDR platform. The built in applications include:
ADS-B Decoder: Decodes aircraft ADS-B data and plots aircraft positions on a map
NOAA APT Decoder: Decodes NOAA weather satellite images (in black and white only)
DVB-S: Decodes and plays Digital TV DVB-S and DVB-S2 video
AIS: Decodes marine AIS data and plots vessel positions on a map
VOR: Decodes VOR aircraft navigational beacons, and plots bearing lines on a map, allowing you to determine your receivers position.
DAB+: Decodes and plays DAB digital audio signals
Radio Astronomy Hydrogen Line: With an appropriate radio telescope connected to the SDR, integrates and displays the Hydrogen Line FFT with various settings, and a map of the galaxy showing where your dish is pointing. Can also control a dish rotator.
Radio Astronomy Solar Observations: Similar to the Hydrogen line app, allows you to make solar measurements.
Broadcast FM: Decoding and playback. Includes RDS decoding.
Noise Figure Measurements: Together with a noise source you can measure the noise figure of a SDR.
Graves Radar Tracker: For Europeans, track a satellite and watch for reflections in the spectrum from the French Graves space radar.
Radio Clocks: Receive and decode accurate time from radio clocks such as MSF, DCF77, TDF and WWVB.
APRS: Decode APRS data, and plot APRS locations and moving APRS enabled vehicles on a map with speed plot.
Pagers: Decode POCSAG pagers
APRS/AX.25 Satellite: Decode APRS messages from the ISS and NO-84 satellites, via the built in decoder and satellite tracker.
Channel Analyzer: Analyze signals in the frequency and time domains
QSO Digital and Analog Voice: Decode digital and analog voice. Digital voice handled by the built in DSD demodulator, and includes DMR, dPMR and D-Star.
Beacons: Monitor propagation via amateur radio beacons, and plot them on a map.
We note that the video doesn't show the following additional features such as an analog TV decoder, the SDRAngel "ChirpChat" text mode, a FreeDV decoder and several other features.
Over on Reddit Ian Grody (u/DutchOfBurdock) has posted about his success in using a modded Android smartphone to run an RTL-SDR Blog V3 and NOAA decoder software all within the phone itself.
In the past we posted about Ian's work in getting rtl_power scans to work in conjunction with the Tasker app, in order to generate automated frequency scans on his phone on the go. His more recent work from the past year includes showing us how it's possible to install Debian chroot on an Android phone, and run Linux software like GQRX, GNU Radio, DSD, rtl_433, multimon-ng and dump1090 directly on the phone with an RTL-SDR.
His latest Reddit post shows that the NOAA-APT decoder also runs well on the Debian chroot, leading to a truly portable NOAA decoding setup. He notes that he is now working on the possibility of Meteor M2 decoding on the phone.
Below is his video from last year demonstrating SDR GQRX and GNU Radio running on the Debain chrooted phone.
There are already many image decoders for the NOAA APT weather satellites available, with the most common and feature rich program being the abandoned freeware "WXtoIMG".
However many people may not know how simple the APT digital signal processing code is. Over on his blog post Dmitrii Eliuseev explains how only 50 lines of Python code are required to decode an image from received APT audio. Dmitrii's post shows how a Hilbert transform is used on the APT audio which is essentially the entire decoding step. This is then followed by a for loop that calculates the pixel luminosity from the decoded data, and plots it onto an image file.
Of course the image is only grayscale (or in Dmitrii's case he decided to use greenscale), but adding false color and various other image enhancements found in advanced software like WXtoIMG are just standard image processing techniques.
Dmitrii concludes with the following:
Interesting to mention, that there are not so many operational radio communication systems in the world, the signal of which can be decoded using 20 lines of code. The NOAA satellites are about 20 years old, and when they finally will retire, the new ones will most likely be digital and format will be much more complex (the new Russian Meteor-M2 satellite is already transmitting digital data at 137 MHz). So those who want to try something simple to decode can be advised to hurry up.
