Title:
Evidence-based sensor tasking for space domain awareness
Evidence-based sensor tasking for space domain awareness
Author(s)
Jaunzemis, Andris D.
Holzinger, Marcus J.
Jah, Moriba K.
Holzinger, Marcus J.
Jah, Moriba K.
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Abstract
Space Domain Awareness (SDA) is the actionable knowledge required to predict, avoid,
deter, operate through, recover from, and/or attribute cause to the loss and/or degradation of
space capabilities and services. A main purpose for SDA is to provide decision-making processes
with a quantifiable and timely body of evidence of behavior(s) attributable to specific
space threats and/or hazards. To fulfill the promise of SDA, it is necessary for decision makers
and analysts to pose specific hypotheses that may be supported or refuted by evidence, some
of which may only be collected using sensor networks. While Bayesian inference may support
some of these decision making needs, it does not adequately capture ambiguity in supporting
evidence; i.e., it struggles to rigorously quantify ‘known unknowns’ for decision makers. Over
the past 40 years, evidential reasoning approaches such as Dempster Shafer theory have been
developed to address problems with ambiguous bodies of evidence. This paper applies mathematical
theories of evidence using Dempster Shafer expert systems to address the following
critical issues: 1) How decision makers can pose critical decision criteria as rigorous, testable
hypotheses, 2) How to interrogate these hypotheses to reduce ambiguity, and 3) How to task a
network of sensors to gather evidence for multiple competing hypotheses. This theory is tested
using a simulated sensor tasking scenario balancing search versus track responsibilities.
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Date Issued
2016-09
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