Paper
3 June 2011 NIR spectroscopy with multivariate calibration and lock-in amplification to detect chemicals concealed behind fabrics
Aamer Saleem, Céline Canal, David A. Hutchins, Roger J. Green
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Abstract
The detection of specific chemicals when concealed behind a layer of clothing is reported using near infrared (NIR) spectroscopy. Concealment modifies the spectrum of a particular chemical when recorded at stand-off ranges of three meters in a diffuse reflection experiment. The subsequent analysis to identify a particular chemical has involved employing calibration models such as principal component regression (PCR) and partial least squares regression (PLSR). Additionally, detection has been attempted with good results using neural networks. The latter technique serves to overcome nonlinearities in the calibration/training dataset, affording more robust modelling. Finally, lock-in amplification of spectral data collected in through-transmission arrangement has been shown to allow detection at SNR as low as -60dB. The work has been shown to both allow detection of specific chemicals concealed behind a single intervening layer of fabric material, and to estimate the concentration of certain liquids.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aamer Saleem, Céline Canal, David A. Hutchins, and Roger J. Green "NIR spectroscopy with multivariate calibration and lock-in amplification to detect chemicals concealed behind fabrics", Proc. SPIE 8018, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XII, 80181I (3 June 2011); https://doi.org/10.1117/12.883839
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Calibration

Near infrared

Data modeling

Hydrogen

Signal to noise ratio

Chemical analysis

Spectroscopy

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