Intelligent Sampling of Hazardous Particle Populations in Resource-Constrained Environments (Postprint)

Abstract

Sampling of anomaly-causing space environment drivers is necessary for both real-time operations and satellite design efforts, and optimizing measurement sampling helps minimize resource demands. Relating these measurements to spacecraft anomalies requires the ability to resolve spatial and temporal variability in the energetic charged particle hazard of interest. Here we describe a method for sampling particle fluxes informed by magnetospheric phenomenology so that, along a given trajectory, the variations from both temporal dynamics and spatial structure are adequately captured while minimizing oversampling. We describe the coordinates, sampling method, and specific regions and parameters employed. We compare resulting sampling cadences with data from spacecraft spanning the regions of interest during a geomagnetically active period, showing that the algorithm retains the gross features necessary to characterize environmental impacts on space systems in diverse orbital regimes while greatly reducing the amount of sampling required. This enables sufficient environmental specification within a resource-constrained context, such as limited telemetry bandwidth, processing requirements, and timeliness.

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Document Details

Document Type
Technical Report
Publication Date
Sep 08, 2017
Accession Number
AD1065718

Entities

People

  • J. P. McCollough
  • John M. Quinn
  • M. Starks
  • W. R. Johnston

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Apogees
  • Artificial Satellites
  • Charged Particles
  • Elliptical Orbits
  • Environment
  • Geosynchronous Orbits
  • Low Earth Orbits
  • Measurement
  • Orbits
  • Particle Flux
  • Particles
  • Space Environments
  • Space Sciences
  • Space Systems
  • Spacecraft
  • Trajectories

Fields of Study

  • Environmental science

Readers

  • Distributed Systems and Data Platform Development
  • Image Processing and Computer Vision.
  • Space/Atmospheric Physics.

Technology Areas

  • Space