Comparison of Novel Heuristic and Integer Programming Schedulers for the USAF Space Surveillance Network

Abstract

Space is a highly congested and contested domain begetting the importance of prioritizing the Space Situational Awareness (SSA) mission, especially that of scheduling and tasking the Space Surveillance Network (SSN). According to the 2004 USSTRATCOM Strategic Directive 505-1 (SD 505-1) the SSN uses centralized tasking, with decentralized scheduling. This research develops and compares novel scheduling model reflecting the 2004 SD 505-1. Novel schedulers were developed to reduce time gaps between observations, prioritize high value space objects, and retain maximum observation quality. In both single and multi-sensor scenarios, these novel schedulers maintained the same, or higher, levels of observation threshold retention in high priority targets, while increasing observation threshold gains in lower categories. Simulations using the novel schedulers showed at least 3 percent improvement in meeting threshold requirements, 12 percent decrease in mean time between observations, and up to 9 percent decrease in maximum time between observations. Finally, these benefits were realized with a nominal increase in processing time for most novel schedulers. Results of this research can educate national policy makers on benefits of proposed upgrades to current and future SSA systems.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 21, 2019
Accession Number
AD1077381

Entities

People

  • Kanit Dararutana

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Apogees
  • Artificial Satellites
  • Computer Programming
  • Detection
  • Detectors
  • Elliptical Orbits
  • Genetic Algorithms
  • Integer Programming
  • Linear Programming
  • Network Protocols
  • Space Debris
  • Space Objects
  • Space Situational Awareness
  • Space Surveillance
  • Systems Engineering
  • United States Strategic Command

Readers

  • Aerospace Engineering.
  • Economics
  • Operations Research

Technology Areas

  • Space
  • Space - Space Objects