Optimal Incorporation of Non-Traditional Sensors into the Space Domain Awareness Architecture

Abstract

The United States Government is the world's de facto provider of space object cataloging data, but is challenged to maintain pace in an increasingly complex space environment. This work advances a multi-disciplinary approach to better understand and evaluate an underexplored solution recommended by national policy, in which current collection capabilities are augmented with non-traditional sensors. System architecting and literature identify likely needs, performance measures, and contributors to a conceptualized Augmented Network. Multiple hypothetical telescope architectures are modeled and simulated on four separate days throughout the year, then evaluated against performance measures and constraints using optimization. Decision analysis and Pareto optimality identify a small, diverse set of high-performing architectures while preserving design flexibility. The efficacy of using the performance measures as proxies for reducing positional uncertainty is also explored. The results suggest a 3.5-times increase in average capacity, 55% improvement in coverage, and 3.5 hour decrease in the average maximum time a space object goes unobserved is achievable if decision-makers adopt the Augmented Network approach. A correlation between performance and positional uncertainty is found, suggesting top architectures can generally achieve a major Space Domain Awareness technical requirement without explicitly conducting an orbit determination routine on simulated collection data.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2021
Accession Number
AD1152177

Entities

People

  • Albert R Vasso

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Cyber
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Apogees
  • Artificial Satellites
  • Astronautics
  • Command And Control
  • Computer Programming
  • Computers
  • Detectors
  • Earth Orbits
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Geography
  • Geosynchronous Orbits
  • Geosynchronous Satellites
  • Neural Networks
  • Optical Detection
  • Payload
  • Space Debris
  • Space Environments
  • Space Force
  • Space Objects
  • Space Situational Awareness
  • United States
  • United States Government
  • United States Strategic Command

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace Engineering.
  • Systems Analysis and Design

Technology Areas

  • Space
  • Space - Space Objects