Research Description

An emerging trend in the space community is a transition from large monolithic vehicles to distributed systems with specialized components. Shifting infrastructure from single spacecraft based missions to multi-agent platforms has the potential to reduce mission costs, increase capabilities, and enable quicker responses to changes in the space environment. Applications such as formation flight, sparse arrays, distributed sensing, and expanded spacecraft services such as inspection, rendezvous, and docking, require accurate models of the dynamics of multiple bodies in space flight. Distributed systems introduce new engineering challenges as well.

As missions migrate away from being based on a single monolithic spacecraft and move towards using multiple specialized cooperative spacecraft, it will become increasingly important to be able to characterize the relative positions and resulting motions of these spacecraft. It is desirable to implement these capabilities in an autonomous form which necessitates that guidance and navigation calculations are performed onboard the spacecraft. For autonomous spacecraft to reliably complete tasks within mission parameters it is necessary to base guidance and navigation algorithms on high fidelity models of relative motion dynamics. The study of relative motion dynamics occupies a very relevant position at the forefront of future space endeavors.

An objective of my research is to investigate the balancing act between accurate relative motion models and the computational cost associated with them. A tradeoff exists between the accuracy of a model and its suitability for onboard implementation. Astrodynamics often requires the use of approximations in order to implement the mathematics in real time. My goal is to recapture some of the dynamics typically lost in using these approximations so that improved relative motion models can be developed.