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21 October 2016 A methodology for the optimisation of a mm-wave scanner
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The need to detect non-metallic items under clothes to prevent terrorism at transport hubs is becoming vital. Millimetre wave technology is able to penetrate clothing, yet able to interact with objects concealed underneath.

This paper considers active illumination using multiple transmitter and receiver antennas. The positioning of these antennas must achieve full body coverage, whilst minimising the number of antenna elements and the number of required measurements. It sets out a rapid simulation methodology, based on the Kirchhoff equations, to explore different scenarios for scanner architecture optimisation.

The paper assumes that the electromagnetic waves used are at lower frequencies (say, 10-30 GHz) where the body temperature does not need to be considered. This range allows better penetration of clothing than higher frequencies, yet still provides adequate resolution.

Since passengers vary greatly in shape and size, the system needs to be able to work well with a range of body morphologies. Thus we have used two very differently shaped avatars to test the portal simulations. This simulation tool allows many different avatars to be generated quickly.

Findings from these simulations indicated that the dimensions of the avatar did indeed have an effect on the pattern of illumination, and that the data for each antenna pair can easily be combined to compare different antenna geometries for a given portal architecture, resulting in useful insights into antenna placement. The data generated could be analysed both quantitatively and qualitatively, at various levels of scale.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. Zoë Stec, Frank J. W. Podd, and Anthony J. Peyton "A methodology for the optimisation of a mm-wave scanner", Proc. SPIE 9993, Millimetre Wave and Terahertz Sensors and Technology IX, 99930F (21 October 2016);

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