This study investigates data mining techniques useful for the health monitoring of spacecraft, focusing on (1) features derived from telemetry parameter time series; (2) derived parameters from auxiliary data sources; (3) Kernel-­‐density estimate (KDE) based data density change detection; (5) Poincaré plot analysis; (6) command effect analysis

The design of new ablator materials is currently performed by testing in an ad-hoc manner. The components are mixed together in the designed manner, and the material is then tested to find the bulk properties. If the bulk properties do not meet the required specifications, a modified mixture is developed and tested until the requirements are met. This approach leads to a very large effort to develop/modify a material towards a specific (new) mission environment.

Background and justification:

Increasing complexity of Software Systems necessitates the focus on system function and behaviour, abstracting from lower-level implementation details of the programming languages. Modelling languages start to find their way into the development process, from requirements specification and system-software co-engineering, up to operations, through development and verification. Use of models increases the level of specification formality and provides a possibility for model simulation and formal analysis to verify certain aspects of the system from the early lifecycle phases.

The initial step of the analysis is represented by the definition of the GNSS capabilities and receiver requirements in the environment of interest. The service volume concept has been introduced to this aim, and recent studies pointed out the interest to define and include GNSS performance above the altitude of the constellation itself [1], [2]. It is well known that signals, even if primarily broadcast from GNSS sources in order to serve Earth surface and proximity (i.e. with a beam directed nadir), are available at a limited extent also above the constellation.

The main purpose of this project, as mentioned in the SoW, was to analyse historical mission data and search for new features which would be useful in the telemetry checking, command verification and procedure writing process in the future.
Features of a signal (or parameter in this context) are defined as characteristics that can be measured or calculated over a given time window (such as mean, standard deviation or minimum of a signal).

There is a need to achieve optimal cost effectiveness from remote sensing missions. Concurrently, a key scientific need in remote sensing is to address the spatial and temporal resolution of atmospheric measurements. Improved temporal resolution observations of the atmosphere – and importantly a reduced latency between observation and delivery to the user – can directly improve weather forecasting services.

The purpose of this GSP activity was to assess the capabilities of non-intrusive diagnostic techniques for internal measurements in ablative materials during PWT tests. This initial steps were to identify the measurements to be performed in relation with high-speed Earth re-entry, and to identify the accessible parameters as well as related diagnostics techniques. For this objective an extensive review of the possible measurement methods, with a focus on non-intrusive diagnostics, has been undertaken.

The Optel-μ Implementation Study on ISS has been set up to assess the feasibility of an IOD (In Orbit Demonstration) of the Optel-μ Space Terminal on the ISS (International Space Station).
The Optel-μ system provides an optical data downlink from a LEO (Low Earth Orbit) S/C to an Optical Ground Station with a data rate up to 2Gbit/s. It is being developed by RUAG Space in the frame of the ARTES program