Statistical Risk Estimation for Communication System Design -- A Preliminary Look

abstract. — Spacecraft are complex systems that involve different subsystems with multiple relationships among them. For these reasons, the design of a spacecraft is a time-evolving process that starts from requirements and evolves over time across different design phases. During this process, a lot of changes can happen. They can affect mass and power at the component level, at the subsystem level, and even at the system level. Each spacecraft has to respect the overall constraints in terms of mass and power: for this reason, it's important to be sure that the design does not exceed these limitations. Current practice in system models primarily deals with this problem, allocating margins on individual components and on individual subsystems. However, a statistical characterization of the fluctuations in mass and power of the overall system (i.e., the spacecraft) is missing. This lack of adequate statistical characterization would result in a risky spacecraft design that might not fit the mission constraints and requirements, or in a conservative design that might not fully utilize the available resources. Due to the complexity of the problem and to the different expertise and knowledge required to develop a complete risk model for a spacecraft design, this article is focused on risk estimation for a specific spacecraft subsystem: the communication subsystem. The current research aims to be a " proof of concept " of a risk-based design optimization approach, which can then be further expanded to the design of other subsystems as well as to the whole spacecraft. The objective of this research is to develop a mathematical approach to quantify the likelihood that the major design drivers of mass and power of a space communication system would meet the spacecraft and mission requirements and constraints through the mission design lifecycle. Using this approach, the communication system designers will be able to evaluate and to compare different communication architectures in a risk trade-off perspective. The results described in this article include a baseline communication system design tool and a statistical characterization of the design risks through a combination of historical mission data and expert opinion contributions. An application example of the communication system of a university spacecraft is presented. 2