Initial Results of Heuristic Guided Orbit Selection for a Low Frequency Radio Interferometric Spacecraft Constellation

A constellation of radio telescope spacecraft can leverage interferometry
to accurately image distant objects throughout
the universe, but mission design must balance among many
interrelated constraints. In particular, the number of craft
and the selection of time-varying orbital parameters play a
pivotal role in determining what interferometric baselines are
feasible with respect to different targets, and thus drives the
breadth and quality of data available to the constellation. The
large combinatorial orbit configuration space and competing
concerns present a challenging problem that is not well addressed
by traditional mission design processes. This paper
describes application of automated optimization methods to
help direct mission design effort to the most promising dynamic
constellation geometries: those that achieve broad interferometric
coverage but remain cost-effective and resilient
to failures. Several automatic heuristic-driven optimization
algorithms representing complementary search strategies
were created to explore among concrete constellation configuration
plans. Evaluation of each candidate constellation
plan was accelerated by efficiently combining precomputed
caches of orbital and interferometric data. Results indicate
that leveraging automated optimization for constellation mission
design is both practical and illuminating: generated solutions
provided both evidence for existing design intuitions
as well as fresh insights into novel configurations.