Timing SDR recordings with GPS

Following a discussion on Twitter about how to use satellite signals to check that distributed receivers are properly synchronized, I have decided to write a post about how to use GPS signals to timestamp an SDR recording. The idea is simple: we do a short IQ recording of GPS signals, and then process those signals to find the GPS time corresponding to the start of the recording. This can be applied in many contexts, such as:

  • Checking if the 1PPS synchronization in an SDR receiver is working correctly.
  • Timestamping an SDR recording without the need of a GPS receiver or 1PPS input, by first recording GPS signals for some seconds and then moving to the signals of interest (this only works if you’re able to change frequency without stopping the sample stream).
  • Measuring hardware delays between the 1PPS input and the ADC of an SDR (for this you need to know the hardware delay between the antenna connector and 1PPS output of your GPSDO).
  • Checking if synchronization is repetitive across restarts or power cycles.

We will do things in a fairly manual way, using a couple of open source tools and a Jupyter notebook. The procedure could certainly be automated more (but if you do so, at some point you might end up building a full fledged GPS receiver!). The post is written with a walk-through approach in mind, and besides the usefulness of timestamping recordings, it is also interesting to see hands-on how GPS works.

Radiometry for DELFI-PQ, EASAT-2 and HADES

On January 13, the SpaceX Transporter-3 mission launched many small satellites into a 540 km sun-synchronous orbit. Among these satellites were DELFI-PQ, a 3U PocketQube from TU Delft (Netherlands), which will serve for education and research, and EASAT-2 and HADES, two 1.5U PocketQubes from AMSAT-EA (Spain), which have FM repeaters for amateur radio. The three satellites were deployed close together with an Albapod deployer from Alba orbital.

While DELFI-PQ worked well, neither AMSAT-EA nor other amateur operators were able to receive signals from EASAT-2 or HADES during the first days after launch. Because of this, I decided to help AMSAT-EA and use some antennas from the Allen Telescope Array over the weekend to observe these satellites and try to find more information about their health status. I conducted an observation on Saturday 15 and another on Sunday 16, both during daytime passes. Fortunately, I was able to detect EASAT-2 and HADES in both observations. AMSAT-EA could decode some telemetry from EASAT-2 using the recordings of these observations, although the signals from HADES were too weak to be decoded. After my ATA observations, some amateur operators having sensitive stations have reported receiving weak signals from EASAT-2.

AMSAT-EA suspects that the antennas of their satellites haven’t been able to deploy, and this is what causes the signals to be much weaker than expected. However, it is not trivial to see what is exactly the status of the antennas and whether this is the only failure that has happened to the RF transmitter.

Readers are probably familiar with the concept of telemetry, which involves sensing several parameters on board the spacecraft and sending this data with a digital RF signal. A related concept is radiometry, where the physical properties of the RF signal, such as its power, frequency (including Doppler) and polarization, are directly used to measure parameters of the spacecraft. Here I will perform a radiometric analysis of the recordings I did with the ATA.

Waterfalls from the December 2021 eclipse frequency measurement

The HamSci Ham Radio Scienze Citizen Investigation community organized earlier this month the December 2021 Eclipse Festival of Frequency Measurement. The goal of this activity was to measure the frequency of HF time signals such as WWV and RWM over the course of ten days. The experiment lasted from December 1 to December 10, so it included the total eclipse over Antarctica of December 4, which happened between 5:29 and 9:37 UTC.

I participated in this activity with my HF station, which consists of a Hermes-Lite 2 beta2 DDC/DUC SDR transceiver and an end-fed random wire antenna about 17 metres long. I used a 10 MHz reference from a GPSDO as described in this post to lock the Hermes-Lite 2 sampling clock. Instead of measuring frequency in real time, I recorded IQ data at 200 sps for the WWV carrier at 5000, 10000 and 15000 kHz and for the RWM carrier at 4996, 9996 and 14996 kHz, so that the data could be post processed later with any kind of algorithms. I have published my recordings in the “December 2021 Eclipse Festival of Frequency Measurment IQ recording by station EA4GPZ” dataset in Zenodo.

In this post I process the IQ recordings to produce waterfalls that give us an overview of the data. The frequency measurement will be done in a later post.

Imaging Cygnus A at 8.45 GHz with ATA

Earlier this year, I published a post showing our results of the interferometric imaging of Cassiopeia A and Cygnus A at 4.9 GHz with the Allen Telescope Array. Near the end of July, I decided to perform more interferometric observations of Cygnus A at a higher frequency, in order to obtain better resolution. I chose a frequency of 8.45 GHz because it is usually a band clean of interference (since it is allocated to deep space communications), it is used by other radio observatories, so flux densities can be compared directly with previous results, and because going higher up in frequency the sensitivity of the old feeds at ATA starts to decrease.

This post is a summary of the observations and results. The code and data is included at the end of the post.

Rain backscatter on 10 GHz

Yesterday we had a strong storm in Madrid at around 16:30 UTC. The storm was rather short but intense. Seeing the heavy rain, it occurred to me that I might be able to receive the 10 GHz beacon ED4YAE at Alto del León using my QO-100 groundstation (without moving the antenna).

The 10 GHz beacon is 39.4 km away and the direct path to my station is obstructed by some hill in the middle, as shown in the link profile.

Link profile ED4YAE -> EA4GPZ (from HeyWhatsThat.com)

In the countryside just outside town it is possible to receive the beacon, probably because it diffracts on the hills. However, it is impossible for me to receive it directly from home, as there are too many tall buildings in the way.

In fact, when I fired up my receiver as the storm raged, I was able to see the beacon signal, with a huge Doppler spread of some 700 Hz (20 m/s). The CW ID of the beacon was easy to copy.

ED4YAE -> EA4GPZ at 10 GHz via rain backscatter

Then I started recording the signal. As the rain got weaker, it started disappearing, until it faded away completely. This post is a short analysis of the scatter geometry and the recording.

GPS spectrometry at Allen Telescope Array

Over the last few weeks I have been helping the Allen Telescope Array by calibrating the pointing of some of the recently upgraded antennas using the GNU Radio backend, which consists of two USRP N32x devices that are connected to the IF output of the RFCB downconverter. For this calibration, GPS satellites are used, since they are very bright, cover most of the sky, and have precise ephemerides.

The calibration procedure is described in this memo. Essentially, it involves pointing at a few points that describe a cross in elevation and cross-elevation coordinates and which is centred at the position of the GPS satellite. Power measurements are taken at each of these points and a Gaussian is fitted to compute the pointing error.

The script I am using is based on this script for the CASPER SNAP boards, with a few modifications to use my GNU Radio polarimetric correlator, which uses the USRPs and a software FX correlator that computes the crosscorrelations and autocorrelations of the two polarizations of two antennas. For the pointing calibration, only the autocorrelations are used to measure Stokes I, but all the correlations are saved to disk, which allows later analysis.

In this post I analyse the single-dish polarimetric spectra of the GPS satellites we have observed during some of these calibrations.

QO-100 spring eclipse season

A few days ago, the spring eclipse season for Es’hail 2 finished. I’ve been recording the frequency of the NB transponder BPSK beacon almost 24/7 since March 9 for this eclipse season. In the frequency data, we can see that, as the spacecraft enters the Earth shadow, there is a drop in the local oscillator frequency of the transponder. This is caused by a temperature change in the on-board frequency reference. When the satellite exits the Earth shadow again, the local oscillator frequency comes back up again.

The measurement setup I’ve used for this is the same that I used to measure the local oscillator “wiggles” a year ago. It is noteworthy that these wiggles have completely disappeared at some point later in 2020 or in the beginning of 2021. I can’t tell exactly when, since I haven’t been monitoring the beacon frequency (but other people may have been and could know this).

A Costas loop is used to lock to the BPSK beacon frequency and output phase measurements at a rate of 100 Hz. These are later processed in a Jupyter notebook to obtain frequency measurements with an averaging time of 10 seconds. Some very simple flagging of bad data (caused by PLL unlocks) is done by dropping points for which the derivative exceeds a certain threshold. This simple technique still leaves a few bad points undetected, but the main goal of it is to improve the quality of the plots.

The figure below shows the full time series of frequency measurements. Here we can see the daily sinusoidal Doppler pattern, and long term effects both in the orbit and in the local oscillator frequency.

If we plot all the days on top of each other, we get the following. The effect of the eclipse can be clearly seen between 22:00 and 23:00 UTC.

By adding an artificial vertical offset to each of the traces, we can prevent them from lying on top of each other. We have coloured in orange the measurements taken when the satellite was in eclipse. The eclipse can be seen getting shorter towards mid-April and eventually disappearing.

We see that the frequency drop starts exactly as soon as the eclipse starts. In many days, the drop ends at the same time as the eclipse, but in other days the drop ends earlier and we can see that the orange curve starts to increase again near the end of the eclipse. This can be seen better in the next figure, which shows a zoom to the time interval when the eclipse happens, and doesn’t apply a vertical offset to each trace. I don’t have an explanation for this increase in frequency before the end of the eclipse.

The plots in this post have been done in this Jupyter notebook. The frequency measurements have been stored in this netCDF4 file, which can be loaded with xarray.

More 10 GHz sun observations

Back in 2019, I took advantage of the autumn sun outage season of Es’hail 2 to make some observations as the sun passed in front of the fixed 1.2 metre offset dish I have to receive the QO-100 transponders. Using the data from those observations, I estimated the gain of the dish and the system noise. A few weeks ago, I have repeated this kind of measurements in the spring sun outage season this year. This post is a summary of the results.

Interferometric imaging with Allen Telescope Array

In the weekend experiments that we are doing with the GNU Radio community at Allen Telescope Array we usually have access to some three antennas from the array, since the rest are usually busy doing science (perhaps hunting FRBs). This is more than enough for most of the experiments we do. In fact, we only have two N32x USRPs, so typically we can only use two antennas simultaneously.

However, for doing interferometry, and specially for imaging, the more antennas the better, since the number of baselines scales with the square of the number of antennas. To allow us to do some interferometric imaging experiments that are not possible with the few antennas we normally use, we arranged with the telescope staff to have a day where we could access a larger number of antennas.

After preparing the observations and our software so that everything would run as smoothly as possible, on 2021-02-21 we had a 18 hour slot where we had access to 12 antennas. The sources we observed where Cassiopeia A and Cygnus A, as well as several compact calibrators. After some calibration and imaging work in CASA, we have produced good images of these two sources.

Many thanks to all the telescope staff, specially to Wael Farah, for their help in planning together with us this experiment and getting everything ready. Also thanks to the GNU Radio team at ATA, specially Paul Boven, with whom I’ve worked side by side for this project.

This post is a long report of the experiment set up, the software stack, and the results. All the data and software is linked below.

Voyager-1 single dish detection at Allen Telescope Array

This post has been delayed by several months, as some other things (like Chang’e 5) kept getting in the way. As part of the GNU Radio activities in Allen Telescope Array, on 14 November 2020 we tried to detect the X-band signal of Voyager-1, which at that time was at a distance of 151.72 au (22697 millions of km) from Earth. After analysing the recorded IQ data to carefully correct for Doppler and stack up all the signal power, I published in Twitter the news that the signal could clearly be seen in some of the recordings.

Since then, I have been intending to write a post explaining in detail the signal processing and publishing the recorded data. I must add that detecting Voyager-1 with ATA was a significant feat. Since November, we have attempted to detect Voyager-1 again on another occasion, using the same signal processing pipeline, without any luck. Since in the optimal conditions the signal is already very weak, it has to be ensured that all the equipment is working properly. Problems are difficult to debug, because any issue will typically impede successful detection, without giving an indication of what went wrong.

I have published the IQ recordings of this observation in the following datasets in Zenodo: