## Decoding the STEREO-A space weather beacon

STEREO-A is a solar observation satellite in a heliocentric orbit with a period of 346 days (slightly less than the Earth). It was launched in 2006 together with STEREO-B, which failed 2016. STEREO-A is still operational and producing science data. Whenever the spacecraft is not being tracked by the DSN, its X-band downlink at 8443.530 MHz transmits the so-called space weather beacon. This is a low data rate (~633 bits per second) downlink that contains a summary of the instruments data and that can be received by smaller stations (such as AMSAT-DL’s 20 metre antenna in Bochum, which is one of the stations used to track STEREO-A).

Yesterday, Wei Mingchuan BG2BHC shared some recordings of STEREO-A done with a 13 metre antenna in Harbin Institute of Technology. A large portion of these recordings contains the space weather beacon signal, but there is another part where the transmission first goes carrier only and then transmits wideband data (although the SNR and the recording bandwidth are not enough to work with this signal). Apparently, STEREO-A was being tracked by DSS-35 in Canberra between 7:25 and 10:30 UTC, more or less at the same time that Wei was recording.

In this post I analyse the space weather beacon signal in these recordings.

## Connecting the Pluto SDR to an Android phone

I have a couple of ideas in mind that involve connecting an ADALM-Pluto SDR to a phone or tablet. Usually, the Pluto is connected to a PC through USB, and the Pluto acts as an Ethernet device, so that network communications between the PC and Pluto are possible. I want to have the same thing running with my Android phone, which is an unrooted Xiaomi Mi 11 Lite (model M2101K9AG, if anyone is curious).

As usual when trying to do something slightly advanced with Android, this hasn’t worked on the first go, so I’ve spent some time debugging the problem. Long story short, in the end, the only thing I need to make this work is to run

# fw_setenv usb_ethernet_mode ecm
# fw_setenv ipaddr 192.168.89.1

on the Pluto once and reboot (these settings are saved as uBoot environment variables to persistent storage), then enable Ethernet tethering on the phone every time that I connect the Pluto. I can go to the web browser in the phone and check that I can access the Pluto web server at 192.168.89.1.

Hopefully the rest of this post will give useful information about how everything works behind the scenes, as your mileage may vary with other Android devices (or if you try with an iOS device, of which I know next to nothing).

I haven’t seen many people doing this, so the documentation is scarce. PABR did a set up with LeanTRX, the Pluto and an Android phone, but they were running the Pluto in host mode and the Android phone in device mode, and I’m doing the opposite. Note that when you connect a Pluto and phone together, the roles they take will depend on the USB cable. My phone has USB-C, so I’m using a USB-C plug to type-A receptacle cable (USB-C OTG cable) together with the usual USB type-A plug to USB micro-B plug cable (the cable provided with the Pluto). There is also this thread in the ADI forums, but it doesn’t really say anything about Ethernet over USB.

## More QO-100 orbit determination

In a previous post, I showed my orbit determination experiments of the GEO satellite Es’hail 2 using the beacons transmitted from Bochum (Germany) through the QO-100 amateur radio transponder on-board this satellite. By measuring the phase difference of the BPSK and 8APSK beacons, which are spaced apart by 245 kHz in the transponder, we can compute the three-way range-rate between the transmitter at Bochum and my receiver in Spain. This data can then be used for orbit determination with GMAT.

I have continued collection more data for these experiments, so this post is an update on the results.

## Writing GUPPI files with GNU Radio and using SETI tools

GUPPI stands for Green Bank Ultimate Pulsar Processing Instrument. The GUPPI raw file format, which was originally used by this instrument for pulsar observations, is now used in many telescopes for radio astronomy and SETI. For instance Breakthrough Listen uses the GUPPI format as part of the processing pipeline, as described in this paper. The Breakthrough Listen blimpy tools work with GUPPI files or with filterbank files (basically, waterfalls) that have been produced from a GUPPI file using rawspec.

I think that GNU Radio can be a very useful tool for SETI and radio astronomy, as evidenced by the partnership of GNU Radio and SETI Institute. However, the set of tools used in the GNU Radio ecosystem (and by the wider SDR community) and the tools used traditionally by the SETI community are quite different, and even the file formats and some key concepts are unalike. Therefore, interfacing these tools is not trivial.

During this summer I have been teaching some GNU Radio lessons to the BSRC REU students. As part of these sessions, I made gr-guppi, a GNU Radio out-of-tree module that can write GUPPI files. I thought this could be potentially useful to the students, and it might be a first step in increasing the compatibility between GNU Radio and the SETI tools. (The materials for the sessions of this year are in this repository, and the materials for 2021 are here; these may be useful to someone even without the context of the workshop-like sessions for which they were created).

In this post I will show how gr-guppi works and what are the key concepts for GUPPI files, as these files store the output of a polyphase filterbank, which many people from the GNU Radio community might not be very familiar with. The goal of the post is to generate a simulated technosignature in GNU Radio (a CW carrier drifting in frequency) and then detect it using turboSETI, which is a tool for detecting narrowband signals with a Doppler drift.

Before going on, it is convenient to mention that an alternative to this approach is using gr-turboseti, which wraps up turboSETI as a GNU Radio block. This was Yiwei Chai‘s REU project at the ATA in 2021.

## QO-100 orbit determination

In a previous post, I showed my experiment about measuring the phase difference of the 8APSK and BPSK beacons of the QO-100 NB transponder. The main goal of this experiment was to use this data to do orbit determination with GMAT. Over the last week I have continued these experiments and already have started to perform some orbit determination in GMAT.

Here I give an update about several aspects of the experiment, and show how I am setting up the orbit determination.

## Decoding Danuri

Danuri, also known as KPLO (Korean Pathfinder Lunar Orbiter), is South Korea’s first mission to the Moon. This satellite will orbit the Moon in a 100 km altitude polar orbit. Danuri was launched on 2022-08-04 by a Falcon 9 rocket from Cape Canaveral into a ballistic lunar transfer orbit. It transmits telemetry in S-band at 2260.8 MHz. Additionally, it has a high speed downlink at at 8475 MHz for science data. The S-band downlink uses LHCP (left-handed circular polarization), which is a somewhat unusual choice, as most satellites use RHCP.

Yesterday, on 2022-08-05, the CAMRAS PI9CAM team used the 25 metre Dwingeloo radiotelescope to record the S-band downlink from Danuri. It is unclear if they used the correct polarization, but nevertheless the SNR of the signal is very good. The recordings are published in SigMF format in CAMRAS data repository. In this post I analyse the recordings and show how to decode them with GNU Radio.

## Calculating the QO-100 beacons frequency separation

In my previous post I set out to measure the phase difference between the QO-100 8APSK and BPSK beacons. One of the things I mentioned is that the frequency separation between these two beacons was approximately 1.6 Hz larger than the nominal 245 kHz.

A frequency error of a couple of Hz is typical when working with SDRs unless special care is taken. Many SDRs allow choosing the sample rate and centre frequency with great flexibility, but the drawback is that the frequencies that are achieved are often not exactly the ones we indicated. Fractional-N synthesis PLLs are used to generate the sampling clock and local oscillator, so there are small rounding errors in the generated frequencies.

With enough knowledge of how the SDR hardware works and how it is configured, it is possible to determine these frequency errors exactly, as a rational number $$p/q$$ that we can calculate explicitly, multiplied by the reference frequency of the SDR. Then we can use this exact value to correct our measurements.

I have asked Mario Lorenz DL5MLO and Kurt Moraw DJ0ABR the details of how the beacons are generated in the Bochum groundstation. Two ADALM Pluto‘s are used: one generates the CW and BPSK beacons, and the other generates the 8APSK multimedia beacon. With the data they have given me, I have been able to compute the frequency separation of the 8APSK and BPSK beacons exactly, and the result matches well my experimental observations.

In this post we will look at how the fractional-N synthesis calculations for the Pluto can be done. Since the Pluto uses an AD9363 RFIC, these calculations are applicable to any product using one of the chips from the AD936x family, and to the FMCOMMS3 evaluation board.

## Measuring the QO-100 beacons phase difference

Since a couple months ago, the QO-100 NB transponder has now two digital beacons being transmitted continuously: the “traditional” 400 baud BPSK beacon, and the new 2.4 kbaud 8APSK multimedia beacon. This transponder is an amateur radio bent-pipe linear transponder on board the Es’hail 2 GEO satellite. It has an uplink at 2400.25 MHz, a downlink at 10489.75 MHz, and 500 kHz bandwidth. The two beacons are transmitted from the AMSAT-DL groundstation in Bochum, Germany, with a nominal frequency separation of 245 kHz.

In some posts in the last few years (see this, for instance), I have been measuring the frequency of the BPSK beacon as received by my grounstation in Madrid, Spain. In these frequency measurements we can see the daily Doppler curve of the satellite, which is not completely stationary with respect to the surface of Earth. However, we can also see the frequency variations of the local oscillator of the transponder (including some weird effects called “the wiggles“). For this reason, the frequency of the BPSK beacon is not an ideal measurement for orbit determination, since it is contaminated by the onboard local oscillator.

If we measure the frequency (or phase) of the 8APSK and BPSK beacons and subtract the two measurements, the effects caused by the transponder local oscillator cancel out. The two beacons have slightly different Doppler, because they are not at the same frequency. The quantity that remains after the subtraction is only affected by the movement of the satellite.

Bochum and my station use both references locked to GPS. Therefore, the phase difference of the two beacons gives the group delay from Bochum through the transponder to my station. This indicates the propagation time of the signal, which is often known as three-way range. The three-way range is roughly the sum of distances between the satellite and each groundstation (roughly, but not exactly, due to the light-time delay). It is a quantity that is directly applicable in orbit determination.

In this post I present my first results measuring the phase difference of the beacons and the three-way range.

## Trying to observe the Vega-C MEO cubesats

On July 13, the Vega-C maiden flight delivered the LARES-2 passive laser reflector satellite and the following six cubesats to a 5900 km MEO orbit: AstroBio Cubesat, Greencube, ALPHA, Trisat-R, MTCube-2, and CELESTA. This is the first time that cubesats have been put in a MEO orbit (see slide 8 in this presentation). The six cubesats are very similar to those launched in LEO orbits, and use the 435 MHz amateur satellite band for their telemetry downlink (although ALPHA and Trisat-R have been declined IARU coordination, since IARU considers that these missions do not meet the definition of the amateur satellite service).

Communications from this MEO orbit are challenging for small satellites because the slant range compared to a 500 km LEO orbit is about 10 times larger at the closest point of the orbit and 4 times larger near the horizon, giving path losses which are 20 to 12 dB higher than in LEO.

I wanted to try to observe these satellites with my small station: a 7 element UHF yagi from Arrow antennas in a noisy urban location. The nice thing about this MEO orbit is that the passes last some 50 minutes, instead of the 10 to 12 minutes of a LEO pass. This means that I could set the antenna on a tripod and move it infrequently.

As part of the observation, I wanted to perform an absolute power calibration of my SDR (a USRP B205mini) in order to be able to measure the noise power at my location and also the power of the satellite signals power, if I was able to detect them.

## Real time Doppler correction with GNU Radio

Satellite RF signals are shifted in frequency proportionally to the line-of-sight velocity between the satellite and groundstation, due to the Doppler effect. The Doppler frequency depends on time, on the location of the groundstation, and on the orbit of the satellite, as well as on the carrier frequency. In satellite communications, it is common to correct for the Doppler present in the downlink signals before processing them. It is also common to correct for the uplink Doppler before transmitting an uplink signal, so that the satellite receiver sees a constant frequency.

For Earth satellites, these kinds of corrections can be done in GNU Radio using the gr-gpredict-doppler out-of-tree module and Gpredict (see this old post). In this method, Gpredict calculates the current Doppler frequency and sends it to gr-gpredict-doppler, which updates a variable in the GNU Radio flowgraph that controls the Doppler correction (for instance by changing the frequency of a Frequency Xlating FIR Filter or Signal Source).

I’m more interested in non Earth orbiting satellites, for which Gpredict, which uses TLEs, doesn’t work. I want to perform Doppler correction using data from NASA HORIZONS or computed with GMAT. To do this, I have added a new Doppler Correction C++ block to gr-satellites. This block reads a text file that lists Doppler frequency versus time, and uses that to perform the Doppler correction. In this post, I describe how the block works.