Remote sensing systems such as a constellation of satellites periodically observe regions on the surface of the earth to collect visual imagery and other sensory data that is both spatial and temporal. Efficiently scheduling sensing activities on a constellation of satellites is a natural problem that arises while managing these systems. Given a set of satellites, a set of sensing activities with their priorities and timing constraints, the objective of the problem is to assign activities to the satellites over a given time period such that at most one activity is assigned to a satellite at any time and the quality of information collected by the satellites is maximized. This problem is computationally challenging to solve and is NP-Hard. In this research, heuristics are first developed to find feasible solutions based on a greedy approach and by dividing the given time period into smaller blocks of time. To determine the quality of a feasible solution, an integer linear programming approach is also developed. Numerical results show that good feasible solutions can be obtained in the order of seconds on a standard computer for a constellation of up to eight satellites and thousand activities using the proposed algorithms.
['Kaarthik Sundar', 'Jianglei Qin', 'Sivakumar Rathinam', 'Lewis Ntaimo', 'Swaroop Darbha', 'Christopher G. Valicka']
Algorithms for a Satellite Constellation scheduling Problem