Space – Page 5 – Daniel Estévez

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.

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.

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.

A Rust implementation of Galileo OSNMA

Galileo OSNMA (Open Service Navigation Message Authentication) is a protocol that will allow Galileo GNSS receivers to authenticate cryptographically the navigation data that is broadcast by Galileo satellites. The system is currently in a public test phase and according to the roadmap it will begin the initial service in 2023.

This month I have spent some time working in a new Rust library that implements the receiver-side processing of OSNMA. The library is called galileo-osnma. Although there are still some features that are not implemented, and some other future ideas that I have for this library, it has already reached a point where I feel it can be released and used by others. In its present state it is already able to perform all the steps that are needed to check all the OSNMA authentication data that is currently being transmitted by the satellites during the test phase. The library is licensed under a permissive open source license (Apache + MIT, which is common in the Rust ecosystem).

An update about Tianwen-1’s remote sensing orbit

Tianwen-1, the Chinese Mars orbiter, entered its remote sensing orbit on November 8 2021. In a previous post, I gave an overview of the orbit using one month of state vector data collected from the spacecraft’s telemetry by AMSAT-DL using the 20 m antenna at Bochum observatory. AMSAT-DL has continued receiving telemetry almost every day, so in this post we can now look at nearly 4 months of data for the remote sensing orbit.

This orbit is a polar elliptical orbit with 86 deg inclination, a periapsis altitude of 275 km and an apoapsis radius of 14140 km. The orbital period is approximately 2/7 Mars sidereal days plus 170 seconds. This makes the ground track drift slowly towards the west, allowing the spacecraft to scan all the planet’s surface. Additionally, due to orbit perturbations, the argument of periapsis (and hence its latitude) keeps slowly changing with time. This makes possible to scan all of Mars from a low altitude.