The Libre Space Foundation (LSF) has been working on developing IPFS-tiny. A project aimed to bring the InterPlanetary File System (IPFS) to…other planets and Space.

The development of IPFS-tiny is funded by Protocol Labs.

IPFS-tiny is built in C++, and it is operating and file system agnostic. It is designed to work well on embedded systems and resource-limited devices, such as satellites and spacecraft.

IPFS in a nutshell

IPFS is “designed to preserve and grow humanity’s knowledge by making the web upgradeable, resilient, and more open.” This is a vision that we at LSF can identify with, especially when it comes to enhancing knowledge and supporting openness for the interests of all humanity.

The way IPFS goes about achieving that is by using a distributed architecture.

Contrary to traditional file systems that store data in a centralised location, the IPFS distributed network stores and accesses data peer-to-peer. The data is stored across multiple nodes in the network, and this allows for faster and more efficient access to files. As well as increased security and resiliency. Even though some nodes in the network may be unavailable, the data can still be accessed.

This approach bears many benefits. Because files live across the network, this enables the downloading of a file from multiple locations, and thus, it enhances decentralisation. Especially since these files are not managed by one organisation alone. This way, IPFS can be used in decentralised web applications, content distribution, and data archiving. It allows the versioning and caching of data, as well as the creation of permanent web links, and it can potentially transform how we think about and access data online.

IPFS: A closer look

IPFS and Content Addressing

Content addressing plays an integral part in IPFS. This is because files are not identified by their location but by what they comprise. In other words, they are identified by their content. The files added to IPFS are split into smaller chunks, cryptographically hashed, and given a unique fingerprint called a content identifier or CID. This CID acts as a permanent record of the file, as the specific file exists at that exact point in time.

When the time comes for other nodes to lookup for that file, they ask their peer nodes which one is storing the content referenced by the file’s CID. When they view or download the file, they cache a copy of it. This way, they become another provider of the content until their cache is cleared. When the original file is modified, its cryptographic hash becomes different, and it gets a new CID. This means that any file stored on IPFS can neither get tampered with nor censored. Any potential changes made to a file do not overwrite the original content. What is more, common chunks across files are reusable and, thus, help cut down on storage costs.

Thus, each CID request results in the correct file being delivered securely and efficiently and protecting against any malicious actors attempting to manipulate the system. The safety of this approach is facilitated by IPLD.

What is IPLD?

IPLD originally began as a part of IPFS, but over time, it has matured and developed to become a project on its own.  InterPlanetary Linked Data (IPLD) addresses content through hashes as a unified information space where the data is presented as a graph that can verify itself. The graphs are known as Merkle DAGs or Merkle Directed Acyclic Graphs (DAGs).

In Merkle DAGs, the data structure is illustrated as trees bearing nodes where each node has an Identifier. The nodes are self-descriptive, and every other sub-section of the file can describe itself as well. This provides a multitude of significant information, such as the type of file they are, the type of information they store, and their size too. Every time a tiny bit of information is changed, the graph realises that, and it updates itself with a new, precise self-description. Leading, thus, to compatibility backwards as well as forwards as the graphs are self-verifiable. In other words, the same rules and same graph construction will always have the same CID.

IPLD plays an integral part in IPFS. Its role expands, though and becomes even more significant when IPFS-tiny gets into the picture too.

IPFS-tiny

IPFS and IPFS-tiny: Distinguishing between the two

As we have mentioned, IPFS-tiny is a project developed by LSF attempting to bring IPFS to space and other planets. In essence, IPFS-tiny is a smaller version of IPFS, designed to work well on devices with limited resources.

These devices, including micro and nanosatellites, can have limitations in their processing capabilities, as they often rely on microcontroller units (MCUs) for their main processing needs. They also face storage restrictions with flash storage that may result in wear-off issues. All these challenges restrict the use of IPFS with micro and nanosatellites. And this is why the need for IPFS-tiny has arisen.

This clearly points out that IPFS-tiny is different from IPFS. To connect IPFS-tiny to the main IPFS network, a bridge is required to allow for data to be shared between the two. This is where IPLD is helpful, making it possible for IPFS and IPFS-tiny to interact and work together safely and efficiently.

IPFS-tiny and Space!

By utilising the interoperability of IPLD, we can use IPFS-tiny to bring IPFS (and its benefits) to space. This can be achieved by using SatNOGS, a project run and maintained by LSF. SatNOGS is the largest open-source network of satellite ground stations, with more than 400 stations spread in 54 countries across the globe. Let us take a closer look at some scenarios on how this network can be utilised.

Scenario 1: The SatNOGS Network of ground stations can serve as a bridge, allowing satellites to transmit information blocks using IPFS-tiny. However, if one ground station attempts to alter the data, it will be unsuccessful. As the IPLD ensures that even small changes result in a unique file, it is difficult for malicious actors to manipulate the system.

Scenario 2: The network of ground stations could be further enhanced by incorporating additional satellites, creating a cross-satellite system where information could be shared and made readily available. This expands on Scenario 1 by including additional satellite participants in the network, increasing the overall accessibility and distribution of data.

Scenario 3: Another option would be to expand the network of satellites even further by incorporating IPFS into the setup. This would turn the satellites into dedicated storage units for the IPFS network, making it a true InterPlanetary File System with a space-based layer.

Potential Use cases

Micro and nanosatellites generating much data are increasingly used in missions for various applications. A stable operational state of the space segment must be guaranteed for the missions to be able to complete their goals successfully. Since these micro and nanosatellites operate in Low Earth Orbit (LEO), their communication window with the ground stations is highly limited. In this case, using IPFS could significantly benefit these LEO operations by enabling them to exchange data with IPFS-enabled ground stations as the satellites pass over them. As channel resources are essential, IPFS could significantly assist towards that by uploading or downloading only what is necessary or only those parts of a file that have changed.

This approach helps overcome challenges and reliably transmit information, and share and access data easily and efficiently. Turning the network into a Delay Tolerant Network that is designed in such a way as to operate effectively under extreme conditions, large distances, and challenging circumstances. As is often the case with space communications.

IPFS-tiny: Key implementation features

Let us now take a closer look at some of the key implementation features of IPFS-tiny:

• Nanopb for Protobuf support. Nanopb encodes and decodes messages following the format of Protobuf, Google’s Protocol Buffers. This format comes with minimal requirements for RAM and code space as well as statically allocated memory, and it is, thus, suitable for use in microcontrollers.
• ETLCPP/ETL. The ETL is an embedded template library that improves the features of the Standard Template Library (STL). The latter is not suitable for limited resource requirements. This is why in IPFS-tiny, STL-like C++ containers are used, with a static memory model that is a great fit for lower-resource embedded applications. Allowing, thus, for improved performance in limited-resource devices.
• libcppunit-dev for testing and the CMake build system, which is open-source and versatile enough to support different open-source platforms for software development.

All the key implementation features are designed to be compatible with microcontrollers and ensure efficient, reliable, and accurate performance.

IPFS-tiny supported features

IPFS-tiny supports various features, including Multiformats, CID v0 and v1 support, IPLD dag-pb, and an expandable IPLD implementation. This has the ability to easily implement new coding schemes and support basic IPFS operations such as add(), del(), and get().

Next Steps

IPFS-tiny is a project that is under development, and finalising the implementation of the project is the goal. Once it is completed, it will be tested in orbit.  It could fly in space onboard a future QUBIK mission, with SIDLOC and on the SatNOGS-COMMS. Another part of this implementation would have to be to connect IPFS-tiny to IPFS with a bridge through the SatNOGS Network and consider the CCSDS File Delivery Protocol as part of this implementation.

Are we InterPlanetary yet?

The way IPFS is designed supports a vision for data sharing that overcomes boundaries and limitations, enabling a safer and more resilient internet. IPFS-tiny is a more simplified version of IPFS developed to fit the requirements of actual InterPlanetary data sharing. Adapted to the challenging conditions of satellite communications and space, IPFS-tiny is a tool under development that, when completed, will take IPFS to space, making it truly InterPlanetary. Stay tuned…

Libre Space Foundation participates in the REWIRE Research and Innovation Action, which officially started on October 1^st, 2022. The project is funded by the European Commission under Horizon Europe Programme (Grant Agreement No. 101070627) and spans the period of October 2022 – September 2025.

REWIRE envisions a holistic framework for continuous security assessment of open-source and open-specification hardware and software for IoT devices. As well as the development of cybersecurity certification in accordance with the requirements and guidelines of the recent EU Cybersecurity Act. In particular, REWIRE proposes a scalable and multifunctional cybersecurity platform that will ensure security throughout the life of IoT devices. This will be achieved with continuous security auditing, trust computing and theorem proofs for defining a hardware-based microarchitecture for enhanced protection targeting open-hardware/software vulnerabilities.

REWIRE has invested in three carefully selected pilots (Automotive, Smart Cities, Smart Satellites), which can address the ambitious objectives of the project, i.e., a customizable TEE based on RISC-V and micro benchmarking for quick and automated assessment of h/w vulnerability. Thus, REWIRE aims to safeguard the entire workflow of secure processing; from the Deployment and Operation of a software-based System of Systems to their patch management when new exploits have been identified during run-time, by providing new trust management mechanisms towards the auditability and certification of SW/HW open-source specifications.

Libre Space Foundation (LSF) undertakes the demonstration and evaluation of the Smart Satellites Use Case of the REWIRE action. Specifically, Libre Space Foundation will work on specifying the requirements, design, set up and deployment of an indicative “flat-sat” engineering model of a complete satellite. This flat-sat model will be featuring a RISC-V-based Onboard Processor, a Commercial-Off-The-Shelf (COTS) Onboard Data Handling Unit, and an LSF, in-house developed COMMS Subsystem and Ground Segment simulator.

For more information and updates, you can connect with the project at the dedicated LinkedIn Page or on Twitter.

At Libre Space Foundation, we are dedicated to developing and supporting open-source space technology and projects that promote knowledge and improve space operations. Polaris is a project developed with the support of Libre Space Foundation (LSF). It brings together developers, engineers and university students from around the world. A diverse group of people with a shared interest in space and open-source technology. They are the ones working hard on designing, developing and optimising Polaris: a Python-based, Μachine-Learning (ML) tool, developed in an open-source, collaborative way, aimed at applying machine learning to satellite telemetry.

Polaris ML for SpaceOps

The challenge: Satellite operators, during a mission, have to tackle a daunting yet critical task; to monitor and keep track of numerous telemetry parameters to maintain a clear idea of the behaviour of their satellite. They need to comprehend how these parameters interfere with each other and estimate their impact accurately.

The Solution: This is where Polaris ML gets into the picture. It is a command-line based, machine-learning tool providing a satellite-telemetry analysis that can be of great help to satellite operators. The data collected are turned into comprehensive graph visualisations, using machine-learning models to understand and predict a satellite’s behaviour. Other data sources are also converted into valuable information available to spacecraft operators.

Note: Before examining Polaris ML in more detail, allow us to describe briefly how satellite operators handle these issues at the moment. Though satellites are built to be more self-aware nowadays, operators are still required to jump in and evaluate the situation by setting manual limits. This is called the Out-Of-Limit (OOL) technique which analyses and evaluates the behaviour of a satellite by collecting data and raising out-of-limit alarms about the state of a satellite. Consequently, a ‘soft out-of-limit’ alarm indicates a dangerous trend, while a ‘hard out-of-limit’ alarm is indicative of a failure occurring.  At this point, let us clarify that Polaris ML does not seek to replace operators or the techniques already applied. Instead, what Polaris ML is after is to be able to provide assistance and amplify the process. Polaris ML is after becoming a reliable, efficient and complementary solution for Space Operators.

A closer look

Before analysing the project, let us point out that this is a tool under active development, thus, the interface is very likely to change. Allow us now to delve into the different components of Polaris ML.

Polaris ML makes use of the XGBoost algorithm to analyse the relationship and the inter-dependencies between telemetry parameters. The XGBoost library allows for eXtreme gradient boosting. This is an approach enabling new, updated, and better-informed models to be created by predicting the errors of the previous models. Then, both models are added together to deliver a final prediction. Using this approach, Polaris ML predicts every telemetry parameter in a satellite. It then provides a graph illustrating the interdependence between the parameters, depicting the degree to which one parameter affects the other. The importance of telemetry parameters and how these are linked is presented as a web-based, 3D-interface graph. 3d-force-graph is the component used for the graph output.

Polaris ML is made up of these distinct parts:

• polaris fetch: As the name reveals, this part fetches the data from various sources. Including telemetry data from the SatNOGS Network and Space Weather from SWPC (NOAA).
• polaris learn: This part consists of a machine-learning (XGBoost)-based module that analyses the relationship of all the “fetched” data and returns a JSON graph file as the output.
• polaris viz: A 3d graph-based visualisation module providing an intuitive graph representation of the data.
• polaris convert: A tool used to convert graph outputs from “polaris learn” and “polaris viz” into other formats. For now, it only supports the .gexf formats, which is a language utilised for describing complex networks structures, as well as the associated data and their dynamics.

Vinvelivaanilai

Vinvelivaanilai is a Python module that fetches space weather data from servers of SWPC/NOAA. It then stores the data in text files or on the InfluxDB. It also includes functions enabling TLE and OMM parsing (any GP data) and propagating the orbit of a satellite to locate both its position and its velocity at any given time.

Vinvelivaanilai is the word for space weather in Tamil.

Betsi

The word BETSI stands for “Behaviour Extraction for Time-Series Investigation”, and it aims to implement a state-of-the-art model to detect anomalies automatically without any manual intervention. The model for creating the concise representation is called autoencoder, and it utilises deep-learning techniques to detect any anomalies found within the telemetry data.

But what exactly is an anomaly? 

Anomalies are all events that fall outside the spectrum of the nominal behaviour of a system, generating massive shifts in the values of one or more parameters. Anomalies can have a catastrophic impact on the satellite, especially since their spectrum is quite broad, as it may range from a simple change in orientation to a massive explosion. (One can only imagine the impact).

Polaris ML in a nutshell

Polaris is an open-source, python-based solution developed to facilitate space diagnostics and help spacecraft operators investigate anomalies. It aims to support and enhance satellite operators to improve their processes by enabling them to detect spacecraft behaviour and helping them drive their investigations when anomalies occur.

Valuable Resources on how to get started and join

As we plan to take this project to a broader scale and see it developing further and expanding, we have created a list of resources that can help you familiarise yourself with Polaris ML. To start with, these are the Polaris repositories on GitLab. Then, you can check the detailed documentation that is available online as it walks users through the Polaris ML project. There are also several exciting talks and presentations by some of the members of the Project.

• “What the hell was that?-Satellite Behaviour Analysis with machine learning” by Xabier Crespo Alvarez (Open-Source CubeSat Workshop 2020) https://www.youtube.com/watch?v=SxYeLhbY2lU
• “Polaris: Open Source Machine Learning for Spacecraft Operations” by Hugh Brown (PyCascades 2021) https://www.youtube.com/watch?v=0jNMDqTqD2s
• “Polaris: Open Source Deep Learning for Telemetry Behavior and Anomaly Detection” by Redouane Boumghar (CubeSat Developers Workshop 2021) https://www.youtube.com/watch?v=VUeVt8-DFkc

Want to join the community? Find out how you can get in touch with the team

Polaris ML is backed up by a diverse, international team, welcoming people from different continents, cultures and backgrounds. The project is developed in a collaborative, open-source way and is fostered by an inclusive community. If you want to join, you can contact the team at the dedicated Polaris ML element/matrix channel: https://app.element.io/#/room/#polaris:matrix.org. You are welcome to join the channel, introduce yourself and contribute to the discussions there.

Polaris ML and GSoC

The Polaris ML team welcomes students from all over the world, and it is a popular project sought after by students applying for the Google Summer of Code program. Polaris ML participates in the programme for the third year in a row. The entire team has had great experiences with GSoC, and the project itself has expanded due to the support and contribution of the GSoC students. Adithya Venkateswaran, who has created the Vinvelivaanilai library, has been a star student of GSoC and is an integral member of the Polaris team.

What next?

Polaris ML is an aspiring project with great potential; it aims to optimise space diagnostics, reduce operation workload and enhance autonomous spacecraft operations. With the help of machine learning, Polaris ML aims at becoming a reliable, scalable solution for Space Operations. The project is still developing, optimised to deliver even better intuitive graph models, creating valuable and dynamic anomaly reports. Polaris ML is after opportunities to implement and test this solution in future satellite operations. We have already worked with BOBCAT-1  and the QUBIK pair of satellites. Still, as we wish to improve further and expand, collaborations with satellite operators for upcoming missions are welcome. Especially since we want to test further and optimise the solution itself and its key components.

The 2021 CubeSat Developers Workshop is happening in a few days and is organised by Cal Poly, San Luis Obispo, CA, USA. It will be a virtual conference taking place from the 27th to the 29th of April. The CubeSat Developers Workshop (#CubeSatDW) “Working Together” will feature amazing talks and useful workshops. You can find the full schedule of the event here.

To start with, the event this year features a mix of pre-recorded and live sessions and the registration is free for both. For the Keynote Addresses and the Live Q&A Panels, a passcode will be forwarded to you via email, after the registration. By using that passcode, you will be able to join the live discussions. On April 27th, the pre-recorded presentations from the Live Q&A panellists will be released. This will allow for the registrants to view the presentations and prepare the questions before the live Q&A panels. During the event, there will be time available for the attendees to network.

Libre Space Foundation’s strong presence at the 2021 CubeSat Developers Workshop

At Libre Space Foundation we are thrilled to join this year’s CubeSat Developers Workshop with a number of fascinating and significant presentations from many of our projects. No day of the event will pass without a presentation from a Libre Space Foundation project. With Day #1 featuring two projects of ours. Let us take a more detailed look at the Libre Space Foundation presentations and our speakers:
On Tuesday the 27th of April, Day #1 of the event there are two LSF-related presentations:

• “I hunt satellites”: crowdsourced satellite telemetry collection with SatNOGS
  by Corey Shields | Libre Space Foundation
  and
• “MetaSat: An Open Metadata Toolkit for SmallSat Missions”
  by Daina Bouquin | Harvard-Smithsonian Center for Astrophysics

On Wednesday the 28th of April, Day #2 of the Event:

• “Polaris: open-source deep learning for telemetry behavior and anomaly detection”
  by Red Boumghar | Libre Space Foundation

And on Thursday the 29th of April, Day #3 of the Event:

• “SatNOGS – COMMS: Turnkey Nanosatellite Communications”
  by Manolis Surligas | Libre Space Foundation

We are very excited and looking forward to enjoying all the presentations featuring at the event.
Save the dates and join us at the 2021 CubeSat Developers Workshop virtual conference.

See you online!

We are proud to announce that Libre Space Foundation has been accepted as a member of the International Astronautical Federation! We are excited to be part of such a great community with which we share a love for Space, Space exploration and research.

International Astronautical Federation and Libre Space Foundation

IAF aims at “Connecting @ll Space People” bringing together organisations, universities, space agencies, research institutions and individuals with a profound interest in space. It has managed to successfully build a community, A space-faring world cooperating for the benefit of humanity. It does so through establishing collaborations and partnerships, by creating events and educating the public so that scientific knowledge and information are shared and spread for everyone to acquire. Libre Space Foundation works hard towards bringing space exploration closer to the public, enabling research and supporting education through all of its projects. We believe that Space is humanity’s future and that space should be accessible to all. This is why we support openness in space tech development and data distribution so that knowledge about Space technology and information about space exploration can fuel a better future for all. We both perceive Space as a great opportunity for growth and development but only when it is used to promote peace, knowledge and scientific research. When it is open to everyone to learn and explore freely. We firmly believe that the only way to explore Space to its fullest potential and to benefit humanity is through partnerships and collaborations with shared ideals and dreams. This is why we are very excited to have joined IAF.

A few words about the International Astronautical Federation (IAF)

IAF was founded in 1951 and it is the world’s leading space advocacy body. It counts over 397 members in 69 countries worldwide. Among its members, there are leading space agencies, Universities, companies, research institutions and even museums.

IAF encourages the development of astronautics for peaceful purposes and supports the spreading of knowledge and information about space. It is also the organiser of many thematic events promoting scientific research and knowledge, and it is the organiser of the International Astronautical Congress (IAC) – a significant annual event about space. 2021, marks IAF’s 70th Anniversary. You can read more about IAF’s long history of supporting space and knowledge by reading its History Page.

IAF’s Missions

The International Astronautical Federation has always supported Space, Space exploration and making technical and scientific knowledge available to those interested. Its vision is powerful and its missions are noteworthy and not limited to one field.

• Promoting Cooperation. By organising events and committees it brings experts from all over the world together to collaborate on research and to deal with the issues the industry faces.
• Advancing International Development. Through collaboration between nations, companies, institutions from all over the world.
• Sharing Knowledge. The information collected and the knowledge acquired is shared using many well-established channels.
• Recognizing Achievements. Not only does it keep an eye on the developments regarding space but it also presents awards to the individuals and groups which help move the global space community forward. Each year the IAF awards are amongst the most prestigious awards to be given.
• Preparing the Workforce of Tomorrow. With a range of activities dedicated to nurturing new talent, IAF focuses on knowledge and how to help students and young professionals to grow, learn and evolve.
• Raising Awareness. With the help of its members and its global community, the IAF publications spread around the globe enabling the public to get a closer look at the information about space.

The International Astronautical Federation is a non-profit organisation devoted to spreading knowledge about space and supporting the development of astronautics for the betterment of humanity. With a long history of collaborations and achievements towards making “A space-faring world cooperating for the benefit of humanity,” it works hard to enhance powerful collaborations and build the conditions for a future where space and scientific knowledge prevail.

A few words about Libre Space Foundation

Libre Space Foundation is a non-profit organisation focusing on the development of open-source space technologies. Its mission is to support, promote and enable innovative ideas, projects and initiatives that promote space technology, space exploration and enhance knowledge. All the projects the Foundation runs and its operations are governed by the Principles of the Manifesto. This is why all the projects are open-source, designed and developed under open-source methodologies, operating in transparency and are accessible to everyone. LSF shares its vision of Space being accessible to all humanity not only with a number of organisations, university teams and research institutions but with its global and diverse community of contributors who put their expertise and continuous effort into developing open-source projects and tools. LSF has a wide range of projects under its wings ranging from Machine Learning for satellites (Polaris), satellite missions (UPSAT, QUBIK) to upstream space projects like deployers (PICOBUS) and of course, developing and operating the world’s biggest open-source network of satellite ground stations worldwide (SatNOGS). Libre Space Foundation is proud to be the first-ever member based in Greece to be joining IAF.

In order to understand what gr-leo is and why it is considered to be a powerful, open-source simulation tool, let us first take a look at why it is necessary. Gr-leo is here to fill a gap and to ensure that the quality of communication between a satellite and the ground station is not impaired in any way.

The case

For the success of a satellite mission, there are many conditions that should be taken into consideration. Telecommunication between Earth and a satellite plays a vital role in that success. However, the quality of the telecommunication can be majorly affected by a number of parameters. These can impact and reduce the quality of transmission between Earth and a Satellite. Some of these parameters are: the relative motion of the orbiting satellite, the operating frequencies, the antenna set-up and of course the atmospheric phenomena. In order for the parameters to be predicted, the system should undergo extensive testing under realistic channel conditions and not in a lab environment as that would not be realistic enough.

The solution

Gr-leo is an open-source, simulation tool that facilitates the testing of all these parameters under realistic channel conditions. It allows for the continuous testing of a system’s development, debugging and evaluation. This way the channel conditions are simulated to be realistic enough and indicative of the failures which might affect telecommunication.

The Build-up

Gr-leo is built with the implementation of a GNU Radio module. An Out-of-the-Tree module is a GNU Radio component that no longer lives under the GNU Radio source tree. This means that one can use the basic GNU radio blocks and reconfigure them so as to extend their functionality as they deem necessary. The new blocks created are also available to the community and can be combined with the existing blocks. This is the case with gr-leo. It adheres to the programming notion of blocks as it is found on GNU Radio, but there are new blocks created to suit the project’s needs. GNU Radio provides the community with a vast range of signal processing and channel estimation blocks. However, these can not extensively cater to the needs of a space telecommunication channel. This is why in order to build gr-leo new processing blocks were configured; with each block simulating a different component found in the space channel communication.

A more detailed look into gr-leo

Gr-leo is an open-source, space channel simulator; a tool created to facilitate the simulation of the Earth-Satellite system operation and to explore the possible failures that may occur in space channel telecommunication.

At the core of gr-leo is the channel model definition. The channel model definitions link the different components making up the Earth-Space communication system with a single GNU Radio block. The blocks are synchronous. Their functionality is to pass the signal from the input port to the worker function, alongside a pointer to the output buffer for the duration of satellite observation. A channel model block accepts a list of required parameters that need to be taken into consideration during the channel simulation. Gr-leo is efficient and versatile not only because it creates the appropriate realistic conditions for testing but also because it explores a wide range of parameters in great detail.

Below is an example of a UPSAT flowgraph combining gr-leo and the UPSAT transmitter. Both are included in the gr-satnogs module.

By using the gr-leo module with the GNU Radio Companion integrated blocks we succeed in:

• Defining a satellite and describing its orbit by providing a valid TLE.
• Defining a tracker by specifying its coordinates, the operating frequencies, the antenna type and an observation time-frame.
• Defining the communication channel model and specifying the desired attenuation types which need to be simulated.

Once these parameters are specified, the channel model block attenuates the input signal according to the defined channel model and the orbit of the satellite described by the TLE.

Takeaway

Gr-leo is an open-source space channel simulator developed as a subactivity of SDR Makerspace. It is created to facilitate testing (under realistic conditions) of all those different parameters affecting the quality of transmission between a ground station and an orbiting satellite. Built on the GNU Radio’s programming blocks it adheres to the open-source principles. It extends the use and functionalities of the basic GNU blocks in order to be able to serve the needs and the purposes of a space telecommunication channel. gr-leo is open-source and the blocks created are available to be used by the GNU Radio community. Contrary to other telecommunication channel simulation projects which are proprietary and provided under expensive licenses, gr-leo is open-source, available for everyone in the GNU Radio community to use and it is a powerful and efficient simulator.

If this sounds interesting to you and you wish to find out more you can take a look at the public repo, the wiki and the documentation pages! Feel free to join our community to share your thoughts and ideas!