Tagged: weather satellite

SelfieStick: Combining noisy signals from multiple NOAA APT satellites for clean imagery

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.

Receiving NOAA Global Area Cover (GAC) Images with LeanHRPT

A few weeks ago we posted about how @ZSztanga and @aang254 were able to record and decode Global Area Cover (GAC) images from polar orbiting NOAA weather satellites. GAC images are low resolution, but they provide an image of the entire orbit. The GAC signal is only transmitted over the USA.

A week earlier than @ZSztanga and @aang254 above decoded GAC, another software called LeanHRPT by @Xerbo also implemented a GAC decoder. LeanHRPT is available on Windows, Linux and MacOS, and ready to download binaries are available on the releases page. You'll need the LeanHRPT demodulator too, in order to initially demodulate the signal.

@Xerbo also notes that @dereksgc has also released a useful Python script for predicting NOAA GAC transmissions. It shows when a particular NOAA satellite will begin and end their GAC transmission, as well as the frequency, polarization and elevation of the satellite. 

GAC Transmission Prediction Tool

Global Area Coverage (GAC) Images Decoded from NOAA Satellites

Thank you to @ZSztanga and @aang254 for submitting news about their recent success at decoding the L-Band Global Area Coverage (GAC) signal from polar orbiting NOAA satellites. GAC images are low resolution, and described by NOAA as follows:

Global Area Coverage (GAC) data set is reduced resolution image data that is processed onboard the satellite taking only one line out of every three and averaging every four of five adjacent samples along the scan line.

While it's low resolution, the interesting thing about this data is that you get an image of the entire orbit, not just the data from your current location as you'd receive with the standard 137 MHz APT or L-Band HRPT signal. The catch is that the signal is usually only transmitted over the USA, and you'll need a motorized or hand tracked L-Band satellite dish setup to receive it.

We note that GAC data is not to be confused with the Direct Sounding Broadcast (DSB) signal decoding software we posted about in 2020. 

@ZSztanga has provided some more information about what images are available and who can receive it, and @aang254's tweet below provides some images and additional information:

With @aang254 we decoded GAC from NOAA satellites. It's basically a dump of reduced resolution data from the whole orbit. It includes all the instruments and is transmitted on L-band along with HRPT (mostly over USA, rarely above Europe and only NOAA-19 dumps outside the US). All the decoders are in SatDump.

There is also a schedule available (https://noaasis.noaa.gov/cemscs/polrschd.txt) that includes all the dumps in the upcoming week. It might be a bit hard to interpret, but basically there is a date and the ground station name (SVL stands for Svalbard and it is the only one receivable in Europe). Entries with "GAC" or "PBK" are referring to the GAC transmission.

We've also seen a tweet by @OK9UWU that shows a much longer image of a full orbit.

Demonstrating the New 3D Maps in SDRAngel

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.

Receiving X-Band Images from the Arktika-M1 Arctic Monitoring Satellite

Recently on Twitter @arvedviehweger (Arved) has tweeted that he has successfully received images from the Russian Arctic monitoring satellite known as ARKTIKA-M1, via it's X-band downlink at 7865 MHz. We've reached out to Arved and he's provided the following information on his setup and how he's receiving and decoding the images.

 

The Arktika-M1 satellite is a Russian weather satellite which operates in a HEO orbit. It was launched in February 2021 and has downlinks on multiple bands. The main payload downlink for the imagery is on 7865 MHz (which is also known as the lower X-Band). The satellite only transmits imagery on the X-Band at the moment, it is currently unknown whether it will ever transmit any image data on L-Band.

For Amateur reception that means having access to X-Band RF gear. It usually consists of a low noise pre-amplifier and a downconverter to convert 7865 MHz down to a lower frequency for easier reception with a high bandwidth SDR such as the LimeSDR, a USRP etc.

In my personal setup I use a surplus pre-amplifier made by MITEQ (around 36dB of gain, 1dB NF), my own self-made DK5AV compact X-Band downconverter and a LimeSDR-USB.

The L-Band gear is mounted on top (helix and the pre-amp behind it) and the X-Band gear is right below. From left to right you can see the feed, the downconverter (silver box) and the LNA (mounted to a heatsink and a fan). Recording is done with a LimeSDR-USB running at a sample rate of 50 MSPS. The satellite transmits every 15 minutes once it reaches its apogee, each transmission including the idle period lasts for about 10 minutes. Some pictures of the idle transmission and the actual data transmission can be found in this Tweet, [noting that Idle = more spikes, actual data looks weaker]:

Depending on the geographical location a rather large satellite dish is also required for Arktika-M1. Reception reports all over Europe clearly show that the satellite has a beamed antenna (similar to ELEKTRO-L2).

In my setup I can get away with a 2.4m prime focus dish (made by Channel Master) in North Eastern Germany. It produces around 9 - 10 dB of SNR in the demod of @aang254’s excellent SatDump software. Anything above 5dB will usually result in a decode but since the satellite does not have any FEC you will need more than that for a clean picture. (Image of SNR in Satdump)

A Comprehensive Beginners Guide to HRPT Weather Satellite Reception

Over on his blog Derek (OK9SGC) has recently uploaded a very comprehensive beginners guide to receiving HRPT weather satellite images. HRPT reception can be a little daunting as it requires a good L-Band dish setup which involves choosing and building a feed, and importantly, a way to track the satellite with the dish as it moves across the sky. Tracking can be achieved manually by hand, but that can be very difficult and so a motorized tracking mount is recommended.  

This is unlike the much easier to receive NOAA APT or Meteor LRPT satellite signals in the VHF band which can be received by a V-dipole antenna, or the geostationary GOES HRIT satellites that can be received with a WiFi grid dish and LNA. Both of which do not require tracking.

The advantage of HRPT however, is that you end up with high resolution, close-up, and uncompressed images of the earth. For example Derek notes that NOAA APT gives 4km/px resolution, and Meteor LRPT gives much better 1km/px resolution but it is heavily compressed. Whereas HRPT gives peak resolutions of 1km/px uncompressed. There are also nine satellites in operation sending HRPT, so there are more opportunities to receive.

Derek has created a very comprehensive beginners guide that covers almost everything from purchasing and building the hardware, to finding and tracking the satellites, to setting up the software and decoding images. He notes that an RTL-SDR can be used as the receiver, and that a WiFi dish with GOES SAWBird LNA can work, although the difficult tracking requirements are still there so a smaller offset dish with custom helix feed might be preferred. Derek also provides useful tips, like the fact that the NOAA15 HRPT signal is quite a lot weaker than others.

Images from Dereks HRPT Guide

Elektro-L3 Geostationary Weather Satellite: Easy to Receive LRIT Signal Being Tested

Back in September 2020 we posted about the release of an X-Band decoder for the Elektro-L2 and Elektro-L3 Russian geostationary satellites. These satellites are receivable from Europe, the Middle East, Asia, Africa, South America and Australia. Unlike the HRIT and LRIT L-band transmissions from other geosynchronous satellites like GOES and GK-2A, the X-band Elektro signal is quite difficult to receive, requiring a large dish and more expensive hardware.

However we've recently seen exciting news on Twitter that a new L-band LRIT transmission has been activated on Elektro-L3. Like the Korean GK-2A satellite, this L-band LRIT transmission at 1691 MHz should be much easier to receive requiring only a WiFi dish, SAWBird GOES LNA and an RTL-SDR. We haven't yet confirmed if like GK-2A, the smaller 600 x 400 mm WiFi dish is sufficient, or if Elektro requires the larger 600 x 1000 mm dish size. (See our GOES satellite and GK-2A tutorial for information about the hardware being discussed in this paragraph.)

We note that the Elektro-L3 signal appears to be in testing, and the transmission could be turned on and off, or even turned off permanently. The transmission schedule is also not yet clear although in this recent tweet @HRPTEgor has mapped out some current transmission times for Eletro-L3.

It is hoped that LRIT will also eventually be activated on Elektro-L2, and perhaps even HRIT will be activated too. It is also exciting that more Elektro-L satellites are planned to be launched from 2022 onwards and we expect those to have hopefully LRIT and HRIT transmissions as well. To add further excitement, it is hoped that the L3 LRIT activation means that a LRIT or HRIT signal will be activated on the high elliptical orbit (HEO) northern hemisphere Arctic monitoring ARKTIKA-M1 satellite launched in Feb 2021, as this satellite is derived from the Elektro-L design.

The LRIT activation of Elektro-L3 hopefully means that Europeans should finally have access to a geostationary weather satellite that can be easily received with modest low cost hardware. The current coverage map from Orbitron of the two Elektro satellites is shown below (note that Elektro-L2 LRIT does not appear to have been activated yet).

Elektro-L2 and Elektro-L3 Coverage (Currently only Elektro-L3 LRIT transmissions have been discovered)

Over on Twitter @aang254 has noted that he has already updated his satdump software, adding support for Elektro LRIT decoding, and adding support for all of the available channels and for color. Satdump is available as a binary for Windows, and on Linux can be built from source. Experimentally, Satdump can also be built and run on Android.

The Tweet from @aang254 provides a nice sample image of what can be received.

Using 50 Lines of Python Code to Decode NOAA APT Weather Satellite Images

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.

[Also mentioned on Hackaday]

Simple decoding of NOAA APT satellites in Python