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

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

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

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

Biomedical Engineering

Research output: Contribution to conference › Paper › peer-review

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 language	English (US)
Pages	9.D.4/1-9.D.4/12
State	Published - 2003
Event	The 22nd Digital Avionics Systems Conference - Proceedings - Indianapolis, IN, United States Duration: Oct 12 2003 → Oct 16 2003

Other

Other	The 22nd Digital Avionics Systems Conference - Proceedings
Country/Territory	United States
City	Indianapolis, IN
Period	10/12/03 → 10/16/03

ASJC Scopus subject areas

Aerospace Engineering
Electrical and Electronic Engineering

Cite this

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

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.",

author = "Kerr, {J. Richard} and Luk, {Chiu Hung} and Dan Hammerstrom and Misha Pavel",

year = "2003",

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T1 - Neural net based processor for robust, high-integrity multisensor and synthetic vision fusion

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AU - Luk, Chiu Hung

AU - Hammerstrom, Dan

AU - Pavel, Misha

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

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M3 - Paper

AN - SCOPUS:0344120161

SP - 9.D.4/1-9.D.4/12

T2 - The 22nd Digital Avionics Systems Conference - Proceedings

Y2 - 12 October 2003 through 16 October 2003

ER -

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

Abstract

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ASJC Scopus subject areas

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