For decades, satellites in outerspace have been designed as monolithic systems, which are extremely integrated systems that are aimed to accomplish a set of objectives that match specific user needs. These systems are made up of specific space, control, and ground elements that may go unused or be deactivated once the mission is over. Since space missions have typically been seen as highly customized endeavours, engineers have always worked on developing systems that do not share data and information with other satellites. The space industry is increasingly considering technologies such as Distributed Satellite Systems (DSS), particularly when combined with monolithic satellite systems, where studies indicate that performance is considerably improved while costs are reduced. Recent advancements in Artificial Intelligence (AI) technologies reveal that autonomy is vital in this modern era of space applications. Autonomy is required for enhanced implementation and operation, which can be accomplished by integrating AI techniques to satisfy space mission objectives. These tactics have proved their ability to perform, adapt, and respond to external environment changes without human intervention. Autonomy is provided because it is a critical attribute for steering the new distributed activities that require collaboration and coordinated approaches, allowing new structural functions such as opportunistic coalitions, resource sharing, and in-orbit data services. Trusted Autonomous Satellite Operations (TASO) is required within the DSS infrastructure to accomplish this. This research focuses on developing and using AI technologies for the TASO in DSS, which endows intelligent DSS (iDSS). Specifically focused on the evolution of space and control (on-board) segments required to maximize the performance of iDSS operations through advancements in Cyber-Physical Systems (CPS) and autonomous system designs. The Earth Observation (EO) missions based on iDSS have been investigated and analysed. A generic iDSS design optimisation methodology for EO that provides persistent coverage of the Australian territory is developed from the investigation.