Allan Shtofenmakher, Massachusetts Institute of Technology; Hamsa Balakrishnan, Massachusetts Institute of Technology
Keywords: Space-Based Space Situational Awareness, Space-Based Optical Sensors, Sensor Tasking, Sensor Scheduling, Space Domain Awareness (SDA)
Abstract:
The population of objects in low Earth orbit (LEO) has dramatically increased over the last 15 years and is expected to continue to grow in the years to come. The U.S. Space Surveillance Network (SSN) must monitor and track these resident space objects (RSOs) to prevent in-space collisions, but their rising numbers place additional stress on the limited suite of ground-based radars and telescopes used for space situational awareness (SSA). Proposed solutions include increasing the number and distribution of SSA sensors and improving the algorithms used to allocate those sensors to track RSOs of interest. In this paper, we propose an integer programming formulation for optimally tasking and scheduling a constellation of purpose-built, agile spacecraft with specialized, body-pointed optical sensors dedicated to the LEO catalog maintenance mission. We demonstrate the capability of this strategy in operational-scale simulations featuring up to 20,000 RSOs, derived from real two-line element (TLE) sets, with up to 99.6% of targets successfully tracked by a constellation of 24 such SSA spacecraft over 24 hours. In smaller-scale simulations, we find that the dynamic spatial distribution of space-based systems enables a constellation of 6 such spacecraft to track 10% more LEO targets over a single orbital period than a network of 4 ground-based radar sensors tracking the same set of RSOs over three orbital periods. We likewise find that a constellation of 12 such spacecraft can track several times as many LEO RSOs as a network of 12 ground-based optical sensors, which can be impacted by illumination, weather, and cloud cover. These results motivate investments in additional space-based assets for catalog maintenance, along with the tasking and scheduling algorithms needed to efficiently utilize them.
Date of Conference: September 16-19, 2025
Best Student Paper Award Winner 2025
Track: Space Domain Awareness