Dr. Guy T. Maskall Profile

Dr. Guy T. Maskall

at Agilent Technologies UK Ltd

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Publications (8)

Proceedings Article | 24 October 2016 Presentation + Paper

The performance of spatially offset Raman spectroscopy for liquid explosive detection

Paul Loeffen, Guy Maskall, Stuart Bonthron, Matthew Bloomfield, Craig Tombling, Pavel Matousek

Proceedings Volume 9995, 99950D (2016) https://doi.org/10.1117/12.2241535

KEYWORDS: Raman spectroscopy, Liquids, Backscatter, Glasses, Explosives detection, Hydrogen, Explosives, Sensors, Aerosols, Raman scattering

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Proceedings Article | 24 October 2016 Paper

New capability for hazardous materials ID within sealed containers using a portable spatially offset Raman spectroscopy (SORS) device

Robert Stokes, Mike Bailey, Stuart Bonthron, Thomas Stone, Guy Maskall, Oliver Presly, Eric Roy, Craig Tombling, Paul Loeffen

Proceedings Volume 9995, 999506 (2016) https://doi.org/10.1117/12.2241540

KEYWORDS: Raman spectroscopy, Explosives, Glasses, Opacity, Safety, Luminescence, Silver, Sensors, Psychoactive substances, Cobalt

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Raman spectroscopy allows the acquisition of molecularly specific signatures of pure compounds and mixtures making it a popular method for material identification applications. In hazardous materials, security and counter terrorism applications, conventional handheld Raman systems are typically limited to operation by line-of-sight or through relatively transparent plastic bags / clear glass vials. If materials are concealed behind thicker, coloured or opaque barriers it can be necessary to open and take a sample. Spatially Offset Raman Spectroscopy (SORS)^[1] is a novel variant of Raman spectroscopy whereby multiple measurements at differing positions are used to separate the spectrum arising from the sub layers of a sample from the spectrum at the surface. For the first time, a handheld system based on SORS has been developed and applied to hazardous materials identification. The system - "Resolve" - enables new capabilities in the rapid identification of materials concealed by a wide variety of non-metallic sealed containers such as; coloured and opaque plastics, paper, card, sacks, fabric and glass. The range of potential target materials includes toxic industrial chemicals, explosives, narcotics, chemical warfare agents and biological materials. Resolve has the potential to improve the safety, efficiency and critical decision making in incident management, search operations, policing and ports and border operations. The operator is able to obtain a positive identification of a potentially hazardous material without opening or disturbing the container - to gain access to take a sample - thus improving safety. The technique is fast and simple thus suit and breathing gear time is used more efficiently. SORS also allows Raman to be deployed at an earlier stage in an event before more intrusive techniques are used. Evidential information is preserved and the chain of custody protected. Examples of detection capability for a number of materials and barrier types are presented below.

Proceedings Article | 16 October 2013 Paper

Spatially offset Raman spectroscopy for explosives detection through difficult (opaque) containers

Guy Maskall, Stuart Bonthron, David Crawford

Proceedings Volume 8901, 890104 (2013) https://doi.org/10.1117/12.2031447

KEYWORDS: Raman spectroscopy, Data modeling, Principal component analysis, Hydrogen, Liquids, Glasses, Opacity, Data processing, Explosives detection, Cobalt

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Proceedings Article | 13 October 2011 Paper

Spatially offset Raman spectroscopy (SORS) for liquid screening

Paul Loeffen, Guy Maskall, Stuart Bonthron, Matthew Bloomfield, Craig Tombling, Pavel Matousek

Proceedings Volume 8189, 81890C (2011) https://doi.org/10.1117/12.898109

KEYWORDS: Raman spectroscopy, Hydrogen, Liquids, Glasses, Backscatter, Explosives, Tumor growth modeling, Principal component analysis, Time metrology, Data modeling

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Proceedings Article | 4 June 2011 Paper

Chemical and explosives point detection through opaque containers using spatially offset Raman spectroscopy (SORS)

Paul Loeffen, Guy Maskall, Stuart Bonthron, Matthew Bloomfield, Craig Tombling, Pavel Matousek

Proceedings Volume 8018, 80181E (2011) https://doi.org/10.1117/12.882126

KEYWORDS: Raman spectroscopy, Glasses, Explosives, Opacity, Liquids, Backscatter, Luminescence, Explosives detection, Inspection, Hydrogen

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Proceedings Article | 25 July 2002 Paper

Nonlinear feature extraction for MMW image classification: a supervised approach

Guy Maskall, Andrew Webb

Proceedings Volume 4726, (2002) https://doi.org/10.1117/12.477043

KEYWORDS: Feature extraction, Radar, Data modeling, Image classification, Extremely high frequency, Automatic target recognition, Image transmission, Image resolution, Reflectors, Lead

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Proceedings Article | 22 October 2001 Paper

Nonlinear feature extraction applied to ISAR images of targets for classification

Guy Maskall, Andrew Webb

Proceedings Volume 4379, (2001) https://doi.org/10.1117/12.445374

KEYWORDS: Feature extraction, Radar, Principal component analysis, Data modeling, Image classification, Target recognition, Missiles, Target detection, Binary data, Data acquisition

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Proceedings Article | 19 July 2000 Paper

Nonlinear feature extraction and Bayesian mixture model approaches to target classification using MMW ISAR imagery: a preliminary study

Adrian Britton, Keith Copsey, Guy Maskall, Andrew Webb, Karl West

Proceedings Volume 4033, (2000) https://doi.org/10.1117/12.391844

KEYWORDS: Data modeling, Radar, Polarization, Principal component analysis, Image classification, Feature extraction, Data analysis, Extremely high frequency, Synthetic aperture radar, Modeling

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Showing 5 of 8 publications

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