Abstract
Space and satellite systems are considered to be the most extreme environment to design for and are fraught with engineering difficulty. Performance metrics such as fault tolerance, reliability, pre-determinism and heritage are still high on the list of requirements for all satellite missions. The advent of modem day electronics and miniaturisation, state-of-the-art computing and networking technologies has enabled research into ‘distributed satellite systems’, where multiple spacecraft work collaboratively to perform a mission using intersatellite connectivity. A satellite can be considered one of many nodes in an autonomous and decentralised system, analogous to a mobile ad-hoc network, enabling opportunities in multiple-point sensing, greater communications capabilities, and spacecraft redundancy. Existing satellite constellations can implement distributed satellite system scenarios but provide unpredictable relative ranges and rates due to various space perturbations. This creates a disconnected environment making it difficult to perform distributed mission operations. Without orbit maintenance, limited onboard resources in power and mass could mean lower processing and networking capabilities which need to rise dramatically to meet requirements for these new missions. This thesis investigates the use of an Agent-based distributed computing platform to enable ad-hoc satellites networking.Agents for real-time systems and their applications conclude that, despite being utilised in complex control systems, most Agent middleware is unsuited for mission critical, real-time, networked, embedded systems. Two constellation scenarios are simulated for distributed satellite missions highlighting orbital issues such as relative distance and mission lifetime. Computing requirements for such distributed computing opportunities using intersatellite connectivity and Agent technologies have led to a novel system-on-a-chip design, including a general purpose processor core and a dedicated Java co-processing core to enable hard real-time Agent functionalities and software Agent applications at minimal overhead. Common Agent middleware platforms are compared and a software configuration is chosen with relevant Agent services. A distributed image compression case study is also presented. A picosatellite testbed is also designed to provide realistic computing and power constraints.