Adapting to Change: The CFAR Problem in Advanced Hyperspectral Detection

Author

Schaum, A.

Author_Institution

Naval Res. Lab., Washington

fYear

2007

fDate

10-12 Oct. 2007

Firstpage

15

Lastpage

21

Abstract

Newer, realistic models of targets and backgrounds used in hyperspectral detection do not always lend themselves to a CFAR (constant false alarm rate) formulation. Several advanced techniques are considered here. It is found that incorporating a particular empirically validated method of target evolution permits an exact CFAR version of a large class of advanced detectors based on elliptically contoured distributions. Other validated detectors are considered, for which no closed form normalization exists to convert them to CFAR form. For these a geometrical approach to achieving approximate CFAR performance is described and analyzed.

Keywords

geometry; target tracking; advanced hyperspectral detection; constant false alarm rate formulation; elliptically contoured distributions; geometrical approach; target evolution; Clutter; Detectors; Hyperspectral imaging; Hyperspectral sensors; Laboratories; Matched filters; Pattern recognition; Performance analysis; Radar detection; Testing; CFAR; algorithm; detection; hyperspectral;

fLanguage

English

Publisher

ieee

Conference_Titel

Applied Imagery Pattern Recognition Workshop, 2007. AIPR 2007. 36th IEEE

Conference_Location

Washington, DC

ISSN

1550-5219

Print_ISBN

978-0-7695-3066-6

Type

conf

DOI

10.1109/AIPR.2007.11

Filename

4476118