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Multivariate analysis of statistically poor EDXRD spectra for the detection of concealed explosives
Author(s) -
Luggar R. D.,
Farquharson M. J.,
Horrocks J. A.,
Lacey R. J.
Publication year - 1998
Publication title -
x‐ray spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 45
eISSN - 1097-4539
pISSN - 0049-8246
DOI - 10.1002/(sici)1097-4539(199803/04)27:2<87::aid-xrs256>3.0.co;2-0
Subject(s) - explosive material , multivariate statistics , spectral line , multivariate analysis , diffraction , chemometrics , statistics , analytical chemistry (journal) , materials science , chemistry , mathematics , optics , physics , chromatography , organic chemistry , astronomy
Energy dispersive x‐ray diffraction (EDXRD) has been developed as a tool for the detection of explosives in passenger baggage. The measured spectra result from the combined diffraction from each of the materials within a scattering volume. Multivariate regression was used to identify known components within very noisy data, permitting the rapid detection of explosive materials in the presence of overlying media for security screening applications. Explosives can be positively identified in spectra containing as few as several hundred counts and the error associated with the prediction is consistent from statistically reliable data (10 6 integrated counts) down to spectra containing in the region of 10 3 counts. This analysis can be employed in any situation where qualitative information is required from poor quality spectral data. © 1998 John Wiley & Sons, Ltd.