Title :
Adapting to Change: The CFAR Problem in Advanced Hyperspectral Detection
Author_Institution :
Naval Res. Lab., Washington
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;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop, 2007. AIPR 2007. 36th IEEE
Conference_Location :
Washington, DC
Print_ISBN :
978-0-7695-3066-6
DOI :
10.1109/AIPR.2007.11
