18 May 2012 A small, low-cost, hyperspectral imaging FTIR sensor design for standoff detection applications
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Proceedings Volume 8374, Next-Generation Spectroscopic Technologies V; 83740B (2012); doi: 10.1117/12.919159
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States
Abstract
Hyperspectral imaging (HSI) sensors allow standoff visualization and identification of chemical vapor plumes; however, currently available COTS sensors, which produce very high quality data, are expensive(>$750k), large(>100 L), and massive( >30 kg). Man-portable and UAV based hyperspectral sensor applications require smaller and lighter weight designs. An approach using new technologies, including a microbolometer IR camera, a piezo-electric linear actuator, a FPGA/LAN board, and an embedded multi-core CPU, is presented that seeks to produce similar quality hyperspectral data at a 10x cost reduction, 3x size reduction (<30 L), and a 3x mass reduction (<10 kg for optics and electronics). The design challenges, system overview, and initial performance data measurements from the new spectrometer designs are presented. An overview of the data cube signal processing, including spatial co-adding, re-sampling of the interferogram data point spacing, phase correction, and detection algorithms, is presented. The spectrometer optical design was also tested by temporarily installing a single pixel MCT detector in order to make spectral resolution comparisons with a traditional FTIR spectrometer.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Gruber, Brad Moore, Brian Tercha, Ryan Bowe, "A small, low-cost, hyperspectral imaging FTIR sensor design for standoff detection applications", Proc. SPIE 8374, Next-Generation Spectroscopic Technologies V, 83740B (18 May 2012); doi: 10.1117/12.919159; https://doi.org/10.1117/12.919159
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KEYWORDS
Sensors

Spectroscopy

Infrared cameras

Mirrors

FT-IR spectroscopy

Microbolometers

Clouds

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