Objectives

The main objective is the specification, design, bread-boarding and test of a Ka-band flexible and reconfigurable system-on-module (SoM), centred on a highly integrated hardware and software programmable Radio Frequency (RF) system-on-chip (SoC). It includes the RF, analogue and digital functions.

A scaled engineering model of the proposed Ka-band SoM, based on commercial off-the-shelf (COTS) components, is manufactured. It consists of an assembly of several custom-design printed circuit boards, comprising basically a main board with the monolithic RF SoC (including specific firmware and software) and analogue circuits at a high intermediate frequency and daughter RF boards for the frequency down-conversion and up-conversion from or to Ka-band. It is representative of a Ka-band SoM payload equipment for a small low Earth orbit (LEO) satellite in form, fit and critical functions.

We demonstrate its flexibility, adaptability, and configurability in terms of frequency allocation, channel bandwidth, data rate, waveform, switching, multiplexing, beam forming, etc., through several different applications. Its performance and capabilities in terms of noise figure, frequency stability, phase noise, throughput, bit error ratio (for a regenerative payload), etc, are verified.

The project increases the technology readiness level of the intended Ka-band SoM payload equipment to Technology Readiness Level (TRL) 5.

Challenges

The key challenges in this activity are the miniaturization, integration, and reduced power consumption of state-of-the-art technology, for optimising the size, weight, and power (SWaP) and ensuring the compatibility with small LEO satellites.

We target high-end and reproducible performance, through a largely digital implementation that avoids most of the analogue imperfections, imbalances, temperature variations and ageing effects, and compensates for those of the RF front-ends with digital techniques.

System Architecture

The Ka-band SoM is an advanced software-defined satellite communication payload for small LEO satellites. It provides:

• a receiving antenna sub-system with eight input RF interfaces at Ka-band, with gain control
• a transmitting antenna sub-system with 8 output RF interfaces at Ka-band
• a digital TM/TC interface with the on-board computer

Plan

The activity is organised in four tasks:

• Task 1: Overview of state of the art constellations and comparable products, and their usage of bandwidth and beamforming, followed by derivation of a set of finalised technical specifications and a preliminary design;
• Task 2: A detailed design justified by mathematical and simulated performance, and implementation of the scaled EM;
• Task 3: Validation of function and performance, of the scaled EM;
• Task 4: A technology assessment and development plan

The following milestones applied: SRR, BR, PDR, DDR, TRR, and FR.

Current Status

The SRR datapack is delivered for review.

Companies

Antwerp Space N.V.

http://www.antwerpspace.be/

Belgium

Objectives

The project objectives are to enhance autonomy in decision-making for quality assurance during spacecraft Assembly, Integration, and Testing (AIT). The project focuses on developing an innovative system that integrates augmented reality (AR) and artificial intelligence (AI). By using sensor data from AR devices and AI-based image recognition, the goal is to compare spacecraft CAD models, pictures and videos with the physical assembly and provide the operator with cues to ensure efficiency, precision and accuracy. A collaboration with AI, AR and AIT experts and the use of representative facilities ensures the solution aligns with real-world operational needs. 

Challenges

The project faced some challenges worth noting. OCR struggles with complex backgrounds, and arbitrary alphanumeric sequences. Object Detection’s reliance on real-world data limits flexibility when only CAD models are available. Similarly, 6D Pose Estimation lacks the precision required for certain high-accuracy tasks. Real-time AI processing introduced further issues, including reduced HoloLens application framerate, stream delays causing lag in AI responses, and degraded performance in features like voice dictation.

Additionally, video streaming impacted reliability for external sharing.

System Architecture

The AI4AR system architecture combines a computer and an AR headset to support augmented reality in complex assembly tasks like
satellite integration. 

The computer manages core computational tasks, with the following modules: Detection Module (Identifies and locates objects in the
assembly environment using advanced algorithms); 6D Pose Estimation Module (Ensures precise object and headset positioning for accurate virtual overlays); OCR Module (Extracts text from labels or instruments for validation and contextual guidance); and Communication Module (Enables fast, low-latency data exchange with the AR headset).

The AR headset acts as the operator’s interface, providing augmented visualizations and guidance, capturing real-time visual and depth data for detection and pose estimation; aligning virtual overlays with the user’s perspective and also synchronizing data with the computer for real-time feedback.

Plan

 The project was initially planned to have a full duration of 24 months.

The following different work packages were pursued: WP1 Preliminary Design, which included the “Output 0 (Defined System Scenario)
Review” and the “Output 1 (Finalised Technical Specification) Review”;

WP2 Detailed Design, which included the “Output 2 (Selected Technical Baseline) Review” , the “Output 3 (Verified Detailed Design) Review” and “Output 4 (Implementation and Verification Plan) Review”; WP3 Implementation, which included the Applications Review; and WP4 Validation and Way-Forward, which included the “Output 5 (Verified Deliverable Items and Compliance Statement) Review” and the “Output 6 (Technology Assessment and Development Plan) Review”. 

Current Status

Project completed, all goals achieved.

Companies

LusoSpace

http://www.lusospace.com/

Portugal

IST-ID

https://ist-id.pt/en/

Portugal

LuxSpace SARL

http://www.luxspace.lu/

Luxembourg

OHB System AG

https://www.ohb.de/

Germany

Objectives

The focus of our project was to research, develop, and test a passivation method specifically tailored for Li-ion battery cells to be integrated into small satellites and CubeSats. Our aim was to ensure compliance with the Space Debris Mitigation requirement for passivation, as outlined in the ECSS-U-AS-10C Rev.1 [2] and ISO 24113 6.2.2.3 [3] standards, without introducing any additional risk during normal satellite operations. It was essential for the passivation device to be compatible with commercially available cells commonly used in this type of mission and for satellites operating in both Low Earth Orbit (LEO) and Geostationary Orbit (GEO) applications. 

The project was initiated with the primary objective of addressing the critical issue of space debris and facilitating the implementation of international regulations pertaining to this matter. To validate the efficacy of the proposed approach, realistic degraded battery cells were manufactured and successfully integrated with the prototype electronics. Through extensive testing and refinement, the device has now reached a stage where it is ready to be produced as a proto-flight model for a real demonstration mission.

Challenges

Our research contributes to the broader effort of mitigating the risks associated with space debris. Furthermore, the successful development and implementation of an effective passivation method for Li-ion batteries in small satellites will enhance the overall safety and sustainability of satellite operations in the ever-expanding space environment.

System Architecture

The device has been designed to seamlessly integrate into next-generation small satellites, prioritizing factors such as its compact form factor (PC/104), which ensures compatibility with most CubeSats, its lightweight construction, and its versatile electrical interface.
The incorporation of a reprogrammable microcontroller enables active control over all components of the board, facilitating the establishment of secure and well-defined initial conditions. This feature not only mitigates the risk of accidental satellite activation during ground operations or after the EOL phase but also allows for the reprogramming of the cut-off voltage to accommodate different types of battery cells. Several components, including microcontrollers, have been carefully selected for their radiation hardness to ensure high reliability in operation. The system has undergone extensive validation to ensure its capability to handle loads of up to 155 W (34 V or 8 A), guaranteeing the safe and efficient management of power requirements. Furthermore, the device employs an RS422 interface.

Five candidate cells were initially identified. Key evaluation criteria included energy density, capacity, cycling performance, operating temperature range, safety features, and cost. Based on this assessment, two cell types were ultimately chosen: “Cell A,” a power cell representing LEO missions, and “Cell B,” an energy cell representing MEO and GEO requirements.

Plan

Contract MLS list:

Progress (MS 1) – achieved

Progress (MS2) – achieved

Finale Settlement (MS3) – achieved

Current Status

The project passed the Final Review and it’s officially closed.

Related Links

• IAC Paper
• IEEE Xplore
• CSID 2023

Companies

Argotec

https://www.argotecgroup.com

Italy

ABSL Enersys

https://www.enersys.com/en/products/batteries/absl/absl-space/

United Kingdom

Objectives

The objective is to increase significantly the TRL of a European Metallic Mesh (including network below) for large deployable antenna applications up to Ku-band. Two types of knitting patterns are investigated in terms of RF-performance (reflectivity and PIM), mechanical characteristics and manufacturing processes. A five-meter demonstrator mesh and network has been manufactured and tested.

Challenges

The assembly of a five-meter diameter network structure with mesh. The access ability is challenging because you need to have access to the middle during the assembly which is only possible from one side or via a jigs crane and/or stages.

System Architecture

The carrying net is made of single unidirectional Quartzel rovings between two Polyimide tapes. The carrying net creates faceting triangles. The crossing points are assembled by pins that are inserted into punched holes of the rovings. Within these connecting pins, the tie cables are installed. These consist of an Aramid thread and a spring that tension the upper and lower carrying net to their paraboloid shapes.

The RF-reflective surface of the reflector is made of a mesh manufactured out of gold-plated tungsten.

Plan

The project had a standard approach, design, sample campaign. Based on the result of the sample campaign the demonstrator manufacturing and assembly have been performed. 

Current Status

The required TRL 5 has been fulfilled for the mesh (even TRL 7), the carrying net (even TRL 6), and the tie cables. Based on the performance data gathered from the project activity, several lessons learned have been identified allowing HPS to make further improvements to the design in future follow-up projects.

The ring structure used in MESNET was a rigid assembly which functioned as support jig. The next step to a potential following up project is the combination with a foldable lightweight structure to have a full large deplorable reflector for a potential EQM.
 

Related Links

• Reflective MESH for large deployable reflectors

Companies

HPS GMBH

http://www.hps-gmbh.com

Germany

HPS-RO S.R.L.

https://hps-srl.ro/

Romania

Objectives

• To conduct a system level concept analysis to make sure the DC/DC concept fits the most common product needs.

• To explore the possibilities and drawbacks with digital controlled DC/DC converters

• To explore potential from new technologies such as GaN devices

• To design and test a bread board to evaluate the performance

Challenges

To implement digital control “from scratch” and make it a competitive alternative to traditional analog control.

System Architecture

The architecture consists of a centralized microcontroller that controls three independent DC/DC-converter simultaneously.

Plan

• First step is a conceptual design to be specified and defined.

• Second step is to have a BB design Review.

• Third step is to complete all tests and relevant analysis as input to the final review

Current Status

The project is completed

Companies

Beyondgravity Sweden AB

https://www.beyondgravity.com

Sweden

Objectives

The objective of the STRIVING cIU in-orbit validation/demonstration project was to gain flight heritage for the Beyond Gravity Finland Automotive/COTS component based Interface Electronics circuits. 

The cIU electronics circuits are used in Beyond Gravity Constellation Onboard Computer (cOBC) and constellation Remote Terminal Unit (cRTU) products Power Drive and Analog IO board (PDIO Board).

Challenges

The main technical challenge was the spacecraft payload interface power supply voltage range incompatibility. 

The spacecraft is supplying 18V-25.2V operation voltage to payload and cIU was designed to 22V-38V operation voltage range. The cIU DCDC converter redesign was required.

System Architecture

cOBC/PDIO is based on Automotive/COTS components. All components are TID tested to >30 RAD level by Beyond Gravity team. Design is latchup free, and components are SEE tested.  
The product is highly integrated, providing spacecraft avionics and key interfaces in a single unit. 
The PDIO Key features

• Off-the-shelf solution available at short lead times and an attractive price point

• Fast and easy integration into the cOBC, at the quantity needed, using backplane-less solution

• Highly configurable in software 

• Support for both redundant and single string solutions

• Manufacturing highly automated and optimized for large quantities.

PDIO key functions: 

• DCDC Converter

• CAN bus TM/TC protocol

• Automotive grade, dual core lock step 

• Pulse Matrix Command outputs

• Secondary Voltages

• Stepper Motor drive for SADM and antenna mechanisms

• Magnetorquer drive interface

• Analog and Digital signal acquisition interface.

Plan

The key tasks:

• System design related to cIU interfacing with Spacecraft payload interface. 

• The cIU health telemetry data collection SW implementation

• Additional load and stimuli board design and MAIT

• PFM and FM board MAIT

• cIU interoperability testing against the spacecraft payload interface simulator.

• The cIU health telemetry data analysis after the IOD mission

Current Status

The project was completed without in-orbit demonstration due the cancellation of SITAEL’s STRIVING maiden in-orbit demonstration/validation mission. However, applicable cOBC/PDIO Flight Model deliveries are ongoing. Flight heritage for the product will be achieved on upcoming customer missions.

Related Links

• Power, Drive and Analog IO (PDIO) Datasheet
• Constellation Onboard Computer (cOBC) Datasheet
• cRTU Information

Companies

Beyond Gravity Finland OY

https://www.beyondgravity.com/en

Finland

Objectives

Traditional implementations of Failure Detection, Isolation and Recovery (FDIR) systems rely on monitoring fixed thresholds. As these thresholds are defined before launch, they are conservative and include margins. Moreover, satellite ageing alters the sub-systems’ behaviour and requires adaptation in detection and classification rules. Conversely, data-centric approaches powered by Artificial Intelligence (AI) algorithms can improve anomaly detection timeliness, enable onboard anomaly classification, predictive health monitoring, and a reduced dependency on ground operations.

The Health-AI project develops an innovative AI-powered FDIR system, exploiting recent innovations and developments in Deep Learning technology. The underlying objective is to improve the health monitoring of the different platform sub-systems and software elements of the spacecraft, including ADCS, EPS, and OBC.

The main goals of the activity are:

• Design an AI-based FDIR system for onboard execution that is reusable and highly adaptable in different missions.

• Test and benchmark the designed solution on industry-driven use cases obtained from real flight telemetry, covering a variety of satellite subsystems.

• Assess the impact of AI-based FDIR systems on onboard computational requirements and hardware, including the employment of AI accelerators.

• Demonstrate the execution of the FDIR system on a relevant test bench, targeting a Technology Readiness Level equal to 4.

Challenges

Employing AI algorithms in critical applications poses reliability challenges due to the black-box nature of most machine learning approaches, which makes it difficult to provide proof of minimum guaranteed performance. To mitigate this, it is foreseen that advanced systems will work alongside traditional FDIR to augment performance, rather than substitute existing implementations altogether.

Additionally, data availability and data quality play a crucial role in the development of AI algorithms. In the activity, the role of Tyvak as a satellite integrator and operator is crucial to provide real-mission use cases and data for training and testing the Health-AI system.
 

System Architecture

The proposed system design leverages orbital_OLIVER, an onboard satellite operation automation software developed by AIKO. orbital_OLIVER is an AI-based software designed to enhance the autonomy level of a spacecraft, based on a distributed microservices architecture, which also comprises modules for telemetry forecasting and FDIR.
The Health-AI system leverages two main orbital_OLIVER services, conveniently configured and tailored to address the project use cases. The Sensing Service extracts relevant information from data available onboard through inferences of DL models. Within the Health-AI project, it analyses telemetry streams to detect anomalous behaviour or predict the future evolution of target quantities. The Reasoning Service implements a Knowledge-Based System that performs reasoning tasks, inferring on a structured database of rules and parameters. For the Health-AI project, its role focuses on anomaly classification starting from the platform state and the output of the Sensing Service. It outputs the FDIR events that are then transmitted to the platform.
orbital_OLIVER’s modular design allows a high degree of adaptation to diverse hardware configurations. During the project, the Nvidia Jetson Nano and Ingeniars’ GPU@SAT have been explored for system deployment and testing.
 

Plan

Over a duration of 18 months, the project activity encompasses the detailed definition of technical requirements, use cases, and dataset generation, followed by the complete system design and development. Finally, the project concludes with deployment on target hardware configurations and a thorough testing campaign.

Current Status

The project underwent a successful Final Review on 9th November 2023 and is now completed.
During the activity, the consortium developed an on-board FDIR software for anomaly detection and classification, and telemetry forecasting. The system reached TRL 4 through an extensive testing campaign, which proved its suitability to operate onboard with positive performance. Tested use cases cover different satellite subsystems: ADCS, EPS, and OBC.
The system has been deployed in different configurations on representative hardware, including Artificial Intelligence accelerators. In particular, IngeniArs’ GPU@SAT has been proven suitable to support onboard FDIR.
 

Related Links

• Project webpage on AIKO’s website

Companies

AIKO S.r.l.

https://www.aikospace.com/

Italy

IngeniARS

https://www.ingeniars.com

Italy

Tyvak International S.r.l.

https://tyvak.eu/

Italy