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Performance evaluation and modeling of a Conformal Filter (CF) based real-time standoff hazardous material detection sensor

机译:基于保形过滤器(CF)的实时隔离有害物质检测传感器的性能评估和建模

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Hyperspectral imaging (HSI) systems can provide detection and identification of a variety of targets in the presence of complex backgrounds. However, current generation sensors are typically large, costly to field, do not usually operate in real time and have limited sensitivity and specificity. Despite these shortcomings, HSI-based intelligence has proven to be a valuable tool, thus resulting in increased demand for this type of technology. By moving the next generation of HSI technology into a more adaptive configuration, and a smaller and more cost effective form factor, HSI technologies can help maintain a competitive advantage for the U.S. armed forces as well as local, state and federal law enforcement agencies. Operating near the physical limits of HSI system capability is often necessary and very challenging, but is often enabled by rigorous modeling of detection performance. Specific performance envelopes we consistently strive to improve include: operating under low signal to background conditions; at higher and higher frame rates; and under less than ideal motion control scenarios. An adaptable, low cost, low footprint, standoff sensor architecture we have been maturing includes the use of conformal liquid crystal tunable filters (LCTFs). These Conformal Filters (CFs) are electro-optically tunable, multivariate HSI spectrometers that, when combined with Dual Polarization (DP) optics, produce optimized spectral passbands on demand, which can readily be reconfigured, to discriminate targets from complex backgrounds in real-time. With DARPA support, Chemlmage Sensor Systems (CISS~(™)) in collaboration with Research Triangle Institute (RTI) International are developing a novel, real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS) based on DP-CF technology. RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses recent test and performance modeling results of a RCIS breadboard apparatus.
机译:高光谱成像(HSI)系统可以在存在复杂背景的情况下检测和识别各种目标。但是,当前一代的传感器通常很大,现场成本很高,通常不能实时运行并且灵敏度和特异性有限。尽管存在这些缺点,但基于HSI的智能已被证明是一种有价值的工具,因此导致对此类技术的需求增加。通过将下一代HSI技术转变为更具适应性的配置以及更小,更具成本效益的外形尺寸,HSI技术可以帮助维持美国武装部队以及地方,州和联邦执法机构的竞争优势。在HSI系统功能的物理极限附近运行通常是必要的,并且非常具有挑战性,但通常是通过对检测性能进行严格建模来实现的。我们不断努力改善的特定性能指标包括:在低信号至背景条件下工作;帧速率越来越高;在不理想的运动控制方案下。我们一直在成熟的一种适应性强,成本低,占地面积小的对峙传感器架构,包括使用保形液晶可调滤波器(LCTF)。这些共形滤波器(CF)是电光可调的多变量HSI光谱仪,与双偏振(DP)光学器件结合使用时,可按需产生优化的光谱通带,可以方便地对其进行重新配置,以实时区分目标与复杂背景。在DARPA的支持下,Chemlmage传感器系统(CISS〜(TM))与三角研究所(RTI)国际合作开发了一种新颖的,实时的,自适应的,压缩感测的短波红外(SWIR)高光谱成像技术,称为可重配置基于DP-CF技术的保形成像传感器(RCIS)。 RCIS将解决当前系统的许多缺点,并在解决传感器重量,外形尺寸和成本需求的同时,提高操作敏捷性和检测性能。本文讨论了RCIS面包板设备的最新测试和性能建模结果。

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