Neural net based processor for robust, high-integrity multisensor and synthetic vision fusion

J. Richard Kerr, Chiu Hung Luk, Dan Hammerstrom, Misha Pavel

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

The key aspect to achieving regulatory approval of integrated enhanced vision system (IEVS) will be proof of system integrity, including real-time, automated confidence monitoring; and adequate back-up provisions for situations where such monitoring indicates inadequate integrity. This paper describes the conceptual background, early simulation results, implementation plans, and integrated-systems framework of this technology. Ongoing activities include flight testing with a multiple-sensor suite and associated database references.

Original languageEnglish (US)
Pages9.D.4/1-9.D.4/12
StatePublished - Dec 2 2003
EventThe 22nd Digital Avionics Systems Conference - Proceedings - Indianapolis, IN, United States
Duration: Oct 12 2003Oct 16 2003

Other

OtherThe 22nd Digital Avionics Systems Conference - Proceedings
CountryUnited States
CityIndianapolis, IN
Period10/12/0310/16/03

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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    Kerr, J. R., Luk, C. H., Hammerstrom, D., & Pavel, M. (2003). Neural net based processor for robust, high-integrity multisensor and synthetic vision fusion. 9.D.4/1-9.D.4/12. Paper presented at The 22nd Digital Avionics Systems Conference - Proceedings, Indianapolis, IN, United States.