Satellite Swarm Localization and Control via Random Finite Set Statistics

The proposed novel program will develop and demonstrate an innovative approach to perform real-time relative vehicle localization within a swarm formation with application to communication-less coordination. These objectives are achieved by using Random Finite Sets statistics theory to solve the multiple object tracking problem. The swarm formation localization problem can be formulated as estimating the local intensity function of targets in the near field and developing probabilistic control strategies to track an expected localization state space configuration. Work will focus on refining estimation and control algorithms that can utilize simple measurements, such as range and bearing angle between units, and determine the local environment using feature measurements. Four major tasks are proposed for the development of swarming space vehicle estimation and control: Random Finite Set Localization and Control Theory and Algorithms, Swarm Scenario Implementations, Swarm Design Control and Simulate Toolset, and Swarm Localization and Control Demonstrations. Algorithms developed and analyzed in Phase I will be extended to a wide range of environmental models and swarm vehicle dynamics, including planetary rovers and orbiting spacecraft. The swarm technology will be implemented for real-time integrated system use, with identification of different formation configurations and sensor combination for hardware integration. A swarm design software tool will be created to allow users to utilize the developed technology in proposed mission analysis. Demonstrations of the benefits of the technology will be presented in software and hardware demonstrations, including small mobile robots used to emulate large swarms. Future demonstration missions identified in the Phase II will show the mission enhancements of the operational system.