Real-time, short-wave, infrared hyperspectral conforming imaging sensor for the detection of threat materials

Abstract

There is a growing demand for effective detection of hazardous materials at safe distances in real-time with a high degree of autonomy. In an effort to address this need, ChemImage Sensor Systems (CISS) in collaboration with the Carnegie Mellon Robotics Institute has developed a novel, adaptable, short-wave infrared (SWIR) hyperspectral imaging system for real-time standoff detection of hazardous materials (e.g., explosives, narcotics, etc.). At the heart of this system is the Conformal Filter (CF), which is a liquid crystal (LC)-based tunable filter that transmits multi-band waveforms. Building on concepts of multivariate optical computing, the CF is tuned electro-optically and dynamically to mimic the functionality of a discriminant vector for classification. The resulting integrated detector response approximates the detection response of conventional hyperspectral imaging with only two discrete measurements instead of hundreds to thousands. Real-time detection is achieved by operating two CFs in tandem within a dual polarization (DP) system, which exploits the polarization sensitivity of the LC filters and allows for simultaneous acquisition of the compressed hyperspectral imagery. This improved sampling rate coupled with advanced object recognition, semantic scene understanding, and image reconstruction algorithms enables real-time (i.e., >10 detection fps), on-the-move detection of targets. This paper will discuss the development, characterization, and test results of the first generation SWIR DP-CF imaging sensor, with a focus on its application to explosives and narcotic threat detection.