Planning Algorithm for Multiple Satellite Clusters

A generalized planning methodology for satellite clusters is proposed. The methodology utilizes Hamilton ‐ Jacobi‐Bellman optimality (minimum time or minimum fuel ) to generate quickly a set of maneuvers from an initial stable formation to a e nal stable formation. Maneuvers are selected from the original set based on the maneuver time, fuel, and collision proximity. The e nal maneuvers are calculated by optimizing the switch times using a realisticset of orbital dynamics. The algorithm is developed to be distributed and scaleswell as the number of satellites increases. A minimal level of communication is used because only switch times and collision proximity information are distributed from the planner. An example with four satellites maneuvering in an eccentric orbit (e=0.2) is presented. Results show that optimal cluster maneuvers (minimum time or minimum fuel ) can be generated within minutes, and most of the computational implementation can be accomplished in parallel. I. Introduction S ATELLITE clusters are envisioned as an enabling technology for defense- and science-based missions. NASA’ s Origins program is planning a series of missions that perform spaceborne interferometry to image far off planets for possible life forms. 1 The U.S. Air Force is planning a distributed space-based, synthetic aperture radar mission within the next few years, possibly followed by a full deployment. 2 In each case, clusters of satellites hold the promise of increasing performance and reliability through distribution, while decreasing cost. The latter is a key aspect that will rely on levels of autonomous control algorithms and software currently being developed.

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