- Decoding BGM-1 GMSK telemetry
In my previous post, I analyzed the Doppler of the Blue Ghost Mission 1 S-band telemetry signal during its lunar landing. The mission came to an end on March 16, as night fell on the landing site. During the 14 days that it has been operating on the lunar surface, BGM-1 has been transmitting low-rate GMSK telemetry on S-band at some times, and a high-rate signal on X-band at other times (this is said to be up to 10 Mbps DVB-S2), including some periods of no transmissions, presumably for thermal management.
In this post I will show how to decode the GMSK S-band telemetry signal with GNU Radio. I will use the IQ recording done by CAMRAS with the Dwingeloo 25 m radiotelescope during the landing as an example, since this dataset is publicly available.
The signal is 15360 baud GMSK, with the usual precoder that allows coherent demodulation as OQPSK (see Figure 2.4.17A-1 in the Radio Frequency and Modulation Systems CCSDS Blue Book). The coding is CCSDS concatenated coding with a Reed-Solomon interleaving depth of 4. The frame size is 892 bytes (4 times 223). The frames are CCSDS TM Space Data Link frames, but there is a bug in how the Reed-Solomon interleaving is implemented. The contents of the Space Data Link frames are encrypted, probably using CCSDS SDLS.
- BGM-1 Doppler during the lunar landing
On Sunday March 2, Firefly Aerospace’s Blue Ghost Mission 1 successfully landed on Mare Crisium, becoming the first NASA CLPS mission to perform a fully successful lunar landing. Congratulations to all the team at Firefly for this huge achievement.
Both AMSAT-DL and CAMRAS covered this event live, by receiving the S-band beacon from the lander with the 20 m antenna in Bochum Observatory and the 25 m Dwingeloo radiotelescope respectively, and streaming the waterfall of the signal in YouTube.
In this post I do a quick analysis of the Doppler of the signal received at Bochum and Dwingeloo. Part of the goal of this is to try to answer a question of Jonathan McDowell, who asked if it was possible to determine the exact second of the touchdown from this data. The answer is that this is probably not possible, since for a soft touchdown there is no significant acceleration at touchdown that can be identified in the Doppler curve.
The raw IQ data recorded by AMSAT-DL is not publicly available. The data recorded by CAMRAS can be found here.
- Coding NEON kernels for the Cortex-A53
Some weeks ago, I presented at FOSDEM my work-in-progress high performance SDR runtime qsdr. I showed a hand-written NEON assembly implementation of a kernel that computes \(y[n] = ax[n] + b\), which I used as the basic math block for benchmarks on a Kria KV260 board (which has a quad-core ARM Cortex-A53 at 1.33 GHz). In that talk I glossed over the details of how I implemented this NEON kernel. There are enough tricks and considerations that I could make a full talk just out of explaining how to write this kernel. This will be the topic for this post.
- Decoding HYDRA-T
HYDRA-T is a PocketQube developed and operated by the Spanish start-up Hydra Space. It was launched on SpaceX’s Transporter 12 mission on January 12, and according to this news article (in Spanish), it is very similar to HADES-R, another PocketQube also launched in Transporter 12 and developed by Hydra Space and operated by AMSAT-EA, the Spanish amateur satellite society. While HADES-R is an amateur satellite that carries a transponder for amateur radio communications, HYDRA-T is a commercial satellite which according to the news article carries a payload from the 6G-XTREME CON-SAT project from Universidad Carlos III de Madrid related to 6G deployment.
Some days ago, people in the LibreSpace forums started noticing that HYDRA-T was transmitting telemetry on 437.780 MHz, which is a frequency that belongs to the amateur satellite service 435 – 438 MHz band. This was acknowledged by Félix Páez EA4GQS, who is AMSAT-EA’s president and Hydra Space Software and Satellite Operations Manager. Félix expressed that HYDRA-T should not be transmitting in this frequency even if it has a license to do so.
I could delve more and give my opinion about whether HYDRA-T can rightfully transmit on this frequency, specially given the fact that it is doing so under the Earth Exploration Satellite Service (active) allocation (see the frequency allocation tables from ITU, and the ITU Space Explorer entry for this satellite, which for some reason is listed there as HYDRA-A), which is a whole different usage from a telemetry downlink of a communications satellite. Maybe I will do this another time. In this short post I wanted to focus on the analysis of the short telemetry recording shared by Jan van Gils PE0SAT, and show the similarities between HYDRA-T and HADES-R, as well as previous satellites from AMSAT-EA, for which documentation of their telemetry format is publicly available.
- Decoding IEEE 802.11ah
Since some time, I’ve been thinking about doing something similar to my posts about LTE and 5G NR, but for WiFi (IEEE 802.11). In these posts, I take a signal recording and write a Jupyter notebook from scratch to analyze the signal and decode the data. I use these posts as a way of learning all the details of how these standards work, and I have seen that some people find them very useful.
Recently I was taking a look at a baby monitor camera system, composed by a camera and a monitor screen, since I was curious about how the camera transmits the video. Using Maia SDR, I located the signal at 866 MHz and realized that both the camera and the monitor screen were transmitting OFDM packets of approximately 2 MHz of bandwidth on this frequency. With some cyclostationary analysis, I found that the subcarrier spacing was 31.25 kHz (which works out to be 2 MHz / 64 FFT points), and that the cyclic prefix was 1/4 of the useful symbol duration. This pointed me straight to IEEE 802.11ah (WiFi HaLow), a variant of WiFi designed for the 800 MHz and 900 MHz license-exempt bands. After comparing the packet formats on the 802.11ah standard with the waterfall of my recording, I was sure that this was indeed 802.11ah. What started as a fun and short signal recording experiment has ended up going through the rabbit hole of implementing 802.11ah decoding from scratch in a Jupyter notebook. In this post I explain my implementation and the analysis of this recording.
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