Earth and Space Science (Aug 2020)

Autonomous Detection of Particles and Tracks in Optical Images

  • Andrew J. Liounis,
  • Jeffrey L. Small,
  • Jason C. Swenson,
  • Joshua R. Lyzhoft,
  • Benjamin W. Ashman,
  • Kenneth M. Getzandanner,
  • Michael C. Moreau,
  • Coralie D. Adam,
  • Jason M. Leonard,
  • Derek S. Nelson,
  • John Y. Pelgrift,
  • Brent J. Bos,
  • Steven R. Chesley,
  • Carl W. Hergenrother,
  • Dante S. Lauretta

DOI
https://doi.org/10.1029/2019EA000843
Journal volume & issue
Vol. 7, no. 8
pp. n/a – n/a

Abstract

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Abstract When optical navigation images acquired by the OSIRIS‐REx (Origins, Spectral Interpretation, Resource Identification, and Security‐Regolith Explorer) mission revealed the periodic ejection of particles from asteroid (101955) Bennu, it became a mission priority to quickly identify and track these objects for both spacecraft safety and scientific purposes. The large number of particles and the mission criticality rendered time‐intensive manual inspection impractical. We present autonomous techniques for particle detection and tracking that were developed in response to the Bennu phenomenon but that have the capacity for general application to particles in motion about a celestial body. In an example OSIRIS‐REx data set, our autonomous techniques identified 93.6% of real particle tracks and nearly doubled the number of tracks detected versus manual inspection alone.

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