- Decoding a V16 beacon
The V16 beacon is a car warning beacon that will mandatorily replace the warning triangles in Spain starting in 2026. In the event of an emergency, this beacon can be magnetically attached to the roof of the car and switched on. It has a bright LED strobe light and a connection to the cellular network, which it uses to send its GNSS position to the DGT 3.0 cloud network (for readers outside of Spain, the Spanish DGT is roughly the equivalent of the US DMV). The main point of these beacons is that placing warning triangles far enough from a vehicle can be dangerous, while this beacon can be placed without leaving the car.
There has been some criticism surrounding the V16 beacons and their mandatory usage that will start in January 2026, both for economical and implantation roadmap reasons, and also for purely technical reasons. The strobe light is so bright that you shouldn’t look at it directly while standing next to the beacon (which makes it tricky to pick it up and switch it off), but I have heard that it is not so easy to see in daylight from several hundreds of meters away.
The GNSS geolocation and cellular network service is also somewhat questionable. I purchased a V16 beacon from the brand NK connected (certificate number LCOE 2024070678G1), for no reason other than the fact that it was sold in a common supermarket chain. The instructions in the box directed me to the website validatuv16.com for testing it. In this website you can register the serial number or IMEI of your beacon and your email. Then you switch on the beacon. After 100 seconds the beacon should send a message to the DGT network, and then periodically every 100 seconds. This test service is somehow subscribed to the DGT network, and it sends you an email that contains the message data (GNSS position and battery status) when the DGT network receives it. This is great, but there is no test mode or anything that declares that you are using the beacon just for testing purposes. They only say that you should not leave the beacon on for much longer than what it takes you to receive the email, to avoid the test being mistaken for a real emergency. The fact that the test procedure for this system is literally the same as the emergency procedure is a red flag for me. Additionally, this beacon only includes cellular data service for 12 years, and it is not clear what happens after that.
Technical shortcomings aside, my main interest is how the RF connection to the DGT network works. The beacon I bought has a logo in the box saying that it uses the Orange cellular network. When I tested it, after receiving the confirmation email from the test service, I used a Pluto SDR running Maia SDR and quickly found that the beacon was transmitting NB-IoT on 832.3 MHz. I made a recording of one of the periodic transmissions. In this post I analyse and decode the recording.
- Notes on debugging Rust microcontroller stack usage
A few days ago I was doing some refactoring of my galileo-osnma project. This is a Rust library that implements the Galileo OSNMA (open service navigation message authentication) system. The library includes a demo that runs in a Longan nano GD32VF103 RISC-V microcontroller board. The purpose of this demo is to show that this library can run on small microcontrollers. My refactoring was in principle a simple thing: I was mainly organizing the repository as a Cargo workspace, and unifying the library and some supporting tools into the same crate. However, after the refactor, users reported that the Longan nano software was broken. It would hang after processing some messages. This post is a collection of notes about how I investigated the issue, which turned out to be related to stack usage.
- First analysis of the Lunar GNSS Receiver Experiment data
The Lunar GNSS Receiver Experiment (LuGRE) is a NASA and Italian Space Agency payload that flew in the Firefly Blue Ghost Mission 1 lunar lander. An overview of this experiment can be found in this presentation. The payload contains a Qascom GPS/Galileo L1 + L5 receiver capable of both real time positioning and raw IQ recording, and a 16 dBi high-gain antenna that was pointed towards Earth. For decades the GNSS community has been talking about using GNSS in the lunar environment, and LuGRE has been the first payload to actually demonstrate this concept.
The LuGRE payload ran a total of 25 times over the Blue Ghost mission duration, starting with a commissioning run on 2025-01-15 a few hours after launch and ending with a series of 9 runs on the lunar surface between 2025-01-03 (the day after the lunar landing) and 2025-01-16 (end of mission after lunar sunset). Back in October 15, the experiment data was published in Zenodo in the dataset Lunar GNSS Receiver Experiment (LuGRE) Mission Data. This dataset includes some short raw IQ recordings, as well as output from the real time GNSS receiver (raw observables, PVT, ephemeris and acquisition data). Since I have some professional background implementing high-sensitivity GNSS acquisition algorithms and I find this experiment quite interesting, I decided to do some data analysis, mainly of the raw IQ data.
The initial results of the experiment were presented on September 11 in the ION GNSS+ 2025 conference in a talk titled Initial Results of the Lunar GNSS Receiver Experiment (LuGRE). This talk is only available to registered ION attendees. As I don’t want to resort to my network to scrounge some ION paper credits (which is how proceedings are usually downloaded from the ION website), I haven’t seen anything about this talk besides the abstract. It is quite possible that something of what I will mention here was already presented in this talk. This is what we get as a society for not doing science in a completely public and open way. However, it’s interesting that this also makes my analysis less likely to be biased. I’ve just downloaded some raw IQ data and started looking at it with only basic context about the instrument that produced it and how it was run.
For a first analysis, I have implemented a high-sensitivity acquisition algorithm for the GPS L1 C/A signal in CUDA. I have run this on all the 20 L1 IQ recordings that are available. In this post I present the algorithm and the results.
- Decoding ESCAPADE
ESCAPADE is a twin spacecraft mission that will study the Mars magnetosphere. The science mission is led by UC Berkeley Space Sciences Laboratory and the spacecraft buses were built by Rocket Lab. It was launched on November 13 on the second Blue Origin New Glenn mission NG-2. The spacecraft will spend a year around the Earth-Sun L2 Lagrange point before falling back to Earth for a powered gravity assist that will place them on Hohmann transfer orbit to Mars as the “launch window” to Mars opens. These are the first spacecraft to fly this kind of trajectory.
The day after launch, I used two antennas from the Allen Telescope Array to record the X-band telemetry signals of the two spacecraft, which were approximately 200 thousand km away from Earth. In this post I will show the results of this observation, and how to decode the telemetry. I have published the recording in the dataset “Recording of ESCAPADE X-band telemetry with the Allen Telescope Array shortly after launch” in Zenodo.
- sigmf-toolkit
I have published a new Python package called sigmf-toolkit. It is intended to be a collection of Python tools to work with SigMF files. At the moment it only contains two tools, but I plan on adding more tools to this package as the needs arise. These tools are:
gr_meta_to_sigmf. It converts a GNU Radio metadata file with detached headers to a SigMF file. At the moment it is really simple, and it doesn’t handle capture discontinuities.- sigmf_pcap_annotate. This tool parses a PCAP file using Scapy and it adds annotations to a SigMF file for each packet in the PCAP file.
I find this
sigmf_pcap_annotatetool quite useful when comparing side by side a SigMF file in Inspectrum and a PCAP file in Wireshark to debug issues with digital communications systems. In this post I showcase how this tool can be used.
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