A knowledge based architecture for airborne minefield detection

Author

Deepak Menon

Abstract

"Airborne mine and minefield detection is an active area of research and has seen significant development in the last ten to fifteen years. One of the primary lessons learned during this airborne mid-wave infrared (MWIF) based mine and minefield detection research and development has been the fact that no single algorithm or static detection architecture is able to meet mine and minefield detection performance specifications. This is true not only because of the highly varied environmental and operational conditions under which an airborne sensor is expected to perform but also due to the highly data dependent nature of sensors and algorithms employed for detection. Attempts to make the algorithms themselves more robust to varying operating conditions have only been partially successful. In this thesis, a knowledge-based architecture to tackle this challenging problem is presented"--Abstract, page iii.

Advisor(s)

Agarwal, Sanjeev, 1971-

Committee Member(s)

Kosbar, Kurt Louis
Stanley, R. Joe

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Summer 2005

Pagination

xi, 122 pages

Rights

© 2005 Deepak Menon, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Subject Headings

Expert systems (Computer science) -- DesignInferenceLand mines -- DetectionMines (Military explosives) -- Detection

Thesis Number

T 9100

Print OCLC #

124065920

Recommended Citation

Menon, Deepak, "A knowledge based architecture for airborne minefield detection" (2005). Masters Theses. 4440.
https://scholarsmine.mst.edu/masters_theses/4440