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Virginia Tech

Reactive, Autonomous, Markovian Sensor Tasking in Communication Starved Environments

Abstract

dc:description.abstract

The current Space Traffic Management (STM) community was not prepared for the exponential increase in the resident space object (RSO) population that has taken place over the last several years. The combination of poor communication infrastructure and long scheduling lead times of the Space Surveillance Network (SSN) prevent any type of reactive sensor tasking, which is required in event of anomaly detection. This dissertation was designed to survey extensions to the classical notions of covariance based sensor tasking strategies and develop a methodology for evaluating these techniques. A suboptimal partially observable Markov decision process (POMDP) was used as the simulation framework to test various reward functions and decision algorithms while enabling autonomous, reactive sensor tasking. The goal of this work was used the developed evaluation methodology to perform statistical analyses to determine which metrics were most reliable and efficient for Space Traffic Management (STM) of the geosynchronous Earth orbit (GEO) resident space object (RSO) catalog. Hypotheses were tested against simulations of 873 resident space object (RSO) in geosynchronous Earth orbit (GEO) being tracked by 18 heterogeneous, geographically disperse ground-based electro-optical (EO) sensors. This dissertation evaluates the ability of various sensor tasking metrics to produce rewards that maximize geosynchronous Earth orbit (GEO) catalog coverage capability of a sensor network under realistic communication restrictions.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Aerospace Engineering
Department dc:contributor.department
Aerospace and Ocean Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kadan, Jonathan Evan
Chairs dc:contributor.committeechair
  • Black, Jonathan T.
  • Schroeder, Kevin Kent
Committee members dc:contributor.committeemember
  • Fitzgerald, Riley McCrea
  • Ross, Shane David

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:39238
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/117287

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kadan, Jonathan Evan. Reactive, Autonomous, Markovian Sensor Tasking in Communication Starved Environments. doctoral thesis, Virginia Tech, 2024. https://hdl.handle.net/10919/117287