Band 63, Heft 4 - Space Information Technology/ Guest Editor: Frank Dannemann, Host Editor: Görschwin Fey

The demand for satellites and space systems with ever-increasing avionics requirements is constantly growing, whether in the field of satellite communications or earth observation. Traditional architectures for Data Handling Systems (DHS) on satellites are reaching their limits in terms of flexibility, interoperability and reusability, while slowing down the innovation cycle due to costly qualification. With regard to commercial and industrial solutions, it is evident that ‘plug and play’-like systems based on open standards can overcome the above-mentioned disadvantages. For this reason, this paper describes how open standards could affect the architecture of future satellite DHSs. In particular it shows an transition path from the traditional federated architecture to a centralized but modular architecture based on adapted industrial standards.

In this paper we describe how commercial open standards for embedded systems could affect the architecture of future satellite data handling systems. Traditionally, satellite data handling systems are based on the principles of a federated architecture, i. e. one function is implemented as one box. Each box has its own housing and power supply. In the paper we describe the transition path from the traditional federated architecture to a centralized but modular architecture based on adapted industrial standards. In the presented approach functional modules like on-board computer, Global Navigation Satellite System receiver, interface boards, etc. are combined in a rack communicating via a standard backplane using standardized communication links. The analysis performed during the Advanced Data Handling Architecture study showed that this approach contributes significantly to mass and power reduction (approx. 20 %) of a typical satellite data handling system. Another major point highlighted in the Advanced Data Handling Architecture study is the simplification of Assembly, Integration and Test activities. All this will help space industry to handle increasing system complexity while keeping costs at an acceptable level.

Software modularity and partial qualification capabilities are key enablers to produce cost efficient software in highly regulated domains. The modular concept (called spaceAPPS) described in this paper has been developed in the frame of the OPS-SAT project aiming at missions where flexibility is one of the success factors. spaceAPPS implements a novel software architecture for satellites inspired by the Apps concept of modern smartphones. In the European space domain the operation of a satellite is based on a set of 18 services. Accordingly, in spaceApps these services are mapped to individual Apps. This is not a one-to-one mapping which means that one App implements one or more services. During OPS-SAT ground testing it was demonstrated that functionality could be easily added through a new App or updated through replacing an existing App. Also during OPS-SAT ground testing it could be shown that a failing UserApp did not impact the basic apps to operate the satellite. Thus, it is possible to run applications of different criticality on the same platform. With operating systems supporting time and space separation the risk of failure propagation can be further reduced. The implementation of a partial validation approach, i. e. testing of third-party Apps in a representative environment and not running the validation on the target platform is feasible but was not demonstrated.

Communication has been crucial since the beginning of space exploration. Control information and telemetry data of the space vessels as well as voice and video communication of the crew with the ground control have to be maintained. This paper is a survey for readers new to the topic to get an overview about the current status of space communication in national agencies and standardization bodies and ongoing research in the field. It also gives a short overview about the historical development and finally summarizes the authors’ thoughts about future challenges in space communication.

Machine Learning (ML) is ubiquitously on the advance. Like many domains, Earth Observation (EO) also increasingly relies on ML applications, where ML methods are applied to process vast amounts of heterogeneous and continuous data streams to answer socially and environmentally relevant questions. However, developing such ML- based EO systems remains challenging: Development processes and employed workflows are often barely structured and poorly reported. The application of ML methods and techniques is considered to be opaque and the lack of transparency is contradictory to the responsible development of ML-based EO applications. To improve this situation a better understanding of the current practices and engineering-related challenges in developing ML-based EO applications is required. In this paper, we report observations from an exploratory study where five experts shared their view on ML engineering in semi-structured interviews. We analysed these interviews with coding techniques as often applied in the domain of empirical software engineering. The interviews provide informative insights into the practical development of ML applications and reveal several engineering challenges. In addition, interviewees participated in a novel workflow sketching task, which provided a tangible reflection of implicit processes. Overall, the results confirm a gap between theoretical conceptions and real practices in ML development even though workflows were sketched abstractly as textbook-like. The results pave the way for a large-scale investigation on requirements for ML engineering in EO.