Space, Aerospace & Defence


Satellites are complex systems that are typically well instrumented for monitoring and control purposes. The ever-increasing demands on mission-critical functions, system availability and the rising operational costs of satellites have resulted in an urgent need to autonomously monitor their health and integrity to optimize the life cycle of space missions. This is achieved by combining automation, computational intelligence and model-based design to assess and even predict the health state of the satellites using real-time on-board sensor data (spaced-based) or satellite telemetry (ground-based). GlobVision develops both space- and ground-based state-of-the-art health monitoring and fault diagnosis and prognosis solutions for spacecraft electromechanical systems including sensors and actuators.

The optimization of space mission design and operation requires two important components: (1) High-fidelity simulation of space missions from satellite flight/orbital and attitude dynamics to satellite subsystems and components to space environment; and (2) Reliable and operational software for optimized mission planning. GlobVision develops both high-fidelity spacecraft mission simulators and satellite mission planning systems (MPSs). Our spacecraft mission simulators can execute in two distinct modes: In an accelerated mode (i.e. a pure simulation environment); and a real-time mode for simulating the mission-specific spacecraft flight software (FSW) in the loop (FSW emulation), spacecraft flight computer or processor-in-the-loop (PIL) simulation, and spacecraft hardware-in-the-loop (HIL) simulation. Our MPS solutions generate an optimized (e.g. daily) schedule for a satellite mission to accommodate as many science and military users’ requests as possible while ensuring mission operational and environmental constraints (e.g. power, magnetic field, payload exposure to Sun, etc.) are not violated.  This requires sophisticated scheduling and constrained optimization algorithms that GlobVision has developed in-house over the years. Our MPS solutions are designed in a modular fashion that allows the easy incorporation of operational, mission and payload requirements, constraints, specifications and models into the system; thus enabling easy and rapid customization of the MPS for a newly given mission.

Furthermore, the space environment poses particular risks for both space systems and astronauts, requiring advanced technical expertise to analyse space environment data and indices in order to manage and mitigate those risks. Such data analysis becomes quite overwhelming and time-consuming if it needs to be performed continuously for all space assets and objects (>40,000); thus making automation a necessity rather than a choice! As such, GlobVision has developed Space Situational Awareness (SSA) software that autonomously analyzes space environment data and indices and performs conjunction analysis of space objects to report any environmental and conjunction risks to the operators of space assets.

Finally, GlobVision developed an initial prototype for a Space Medicine Decision Support System (SMDSS) that allows long duration space missions to provide enhanced medical support and autonomy for astronauts.


Whether the challenge lies in performing advanced diagnostics and prognostics on aircraft engines or assessing the irreversible effects of mechanical wear and tear or air load strains and stresses on the aircraft flight control system (FCS), GlobVision has the solution! Our Diagnostics, Prognostics & Health Monitoring (DPHM) solutions for aircraft engines and FCS enhance the safety, availability and operational cost-effectiveness of aircraft by improving aircraft FCS and engine data analysis, achieving early detection of abnormal trends and out-of-spec behaviour, increasing the accuracy of predicting eventual faults and failures, and minimizing false alarm rates and thus unnecessary overhauls. Over the years, we have developed a wide spectrum of model-based and machine learning-based DPHM algorithms for two completely different operational contexts: On-board, where the DHM algorithms execute in real-time on the flight computer respecting the processing and memory constraints of the flight control loop; and on-ground, where analyzing flight data from large fleets of aircraft is required to support state-of-the-art condition-based maintenance (CBM) and “Power-by-the-Hour” concepts of aircraft maintenance and operation.

An important pre-requisite for any DPHM system or maintenance program to remain reliable is (sensor) data integrity. Invalid or poor quality data will always result in wrong decisions (by the DPHM software or flight data analysts and experts) and actions (by the flight controller or maintenance team)! Therefore, it is critical to pre-process all data in order to validate it and verify its integrity prior to using it for other purposes downstream in the processing chain, such as for DPHM and control. We have developed several Data Validation and Qualification (DV&Q) solutions for our customers; not exclusively in the Aerospace sector but also in the Utilities & Infrastructure sector that deal with an abundance of data on a daily basis. With the increased instrumentation of aerial vehicles and their sub-systems; for example, fly-by-wire (FBW) aircrafts and helicopters,  and a drive towards improved safety and operational efficiency, the industry is facing some of the same problems that GlobVision has tackled not only in the aircraft industry but also repeatedly elsewhere, for example in satellites and military land vehicles. Our partners look for reliable, effective and operational solutions and that is precisely what we provide.


The availability and reliability of military assets are of paramount importance for the protection of national interests. This holds true for military spacecraft, aircraft, land and naval vehicles. GlobVison’s advanced and proprietary data mining, data analytics, modeling and model-based design (MBD) expertise has been leveraged for the advanced health monitoring and situational awareness of these critical systems. We have applied our cutting-edge machine learning and MBD methods for fault diagnosis of various types of electro-mechanical components in space, aerial and land vehicles to ensure the Operational Readiness (OR) and safety of such mission-critical military assets/systems for the benefit of the Defence community. We have successfully demonstrated that machine learning and MBD are critical for autonomous diagnostics.