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Proceedings Paper

A simulation study of target detection using hyperspectral data analysis
Author(s): E. Sharifahmadian; Y. Choi; S. Latifi
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Paper Abstract

Target detection is difficult when the target is concealed or placed under ground or water. To detect and identify concealed objects from a distance, the analysis of the HyperSpectral Imaging (HSI) and Wideband (WB) data is studied. While the HSI analysis may render surface information about objects, the WB data can reveal information about inner layers of the object and its content. Two of the challenging issues with object identification using HSI are (i) computational complexity of the analysis and (ii) signature mismatch. Here, the robust matched filter is emphasized for HSI processing. In addition, the wideband technology is utilized to provide more information about concealed target, and to support spectral processing for object uncovering more effectively. During simulation, electromagnetic waves and propagation areas are modeled. In fact, an object is modeled as different layers with different thicknesses. The existence of a target is estimated by the detection of spectral signatures relating to materials used in the target. In other words, the simultaneous presence of spectral signatures corresponding to the main materials of the target in the hyperspectral data helps detecting the target. The reflected higher frequency signals provide information about exterior layers of both an object and the background; in addition, the reflected lower frequency signals provide information about interior layers of the object. To identify different objects, the simulation is performed using HSI, and WB technology at different frequencies (MHz- GHz) and powers. Based on simulation, the proposed method can be a promising approach to detect targets.

Paper Details

Date Published: 20 May 2013
PDF: 13 pages
Proc. SPIE 8744, Automatic Target Recognition XXIII, 874410 (20 May 2013); doi: 10.1117/12.2016365
Show Author Affiliations
E. Sharifahmadian, Univ. of Nevada, Las Vegas (United States)
Y. Choi, Univ. of Nevada, Las Vegas (United States)
S. Latifi, Univ. of Nevada, Las Vegas (United States)

Published in SPIE Proceedings Vol. 8744:
Automatic Target Recognition XXIII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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