Drone detection in the reflective bands: Vis, NIR, SWIR, eSWIR

Joshua Follansbee, Lindsey Wiley, Patrick Leslie, Charles Revello, Ronald Driggers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Target detection and identification are well-studied problems in the visible (VIS) and near infrared (NIR) bands, with recent work focusing on the short wave IR (SWIR) band. The extended SWIR (eSWIR) band (2 to 2.5 μm) offers an advantage over SWIR due to increased atmospheric transmission, while keeping greater angular resolution than the midwave and longwave IR. eSWIR should additionally improve object-sky contrast due to lower background sky path radiance than the SWIR. An analysis of drone signal-To-noise ratio (SNR) and contrast in the reflective bands is presented and compared to an NVIPM model of drone detection performance using equivalent reflectivities.

Original languageEnglish (US)
Title of host publicationInfrared Imaging Systems
Subtitle of host publicationDesign, Analysis, Modeling, and Testing XXXIII
EditorsGerald C. Holst, David P. Haefner
PublisherSPIE
ISBN (Electronic)9781510650886
DOIs
StatePublished - 2022
EventInfrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIII 2022 - Virtual, Online
Duration: Jun 6 2022Jun 12 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12106
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceInfrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIII 2022
CityVirtual, Online
Period6/6/226/12/22

Keywords

  • SNR
  • SWIR
  • contrast
  • drone
  • drones
  • eSWIR
  • infrared
  • reflective bands
  • target detection

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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