Field test results are presented for a prototype long-wave adaptive imager that provides both hyperspectral imagery and contrast imagery based on the direct application of hyperspectral detection algorithms in hardware. Programmable spatial light modulators are used to provide both spectral and spatial resolution using a single element detector. Programmable spectral and spatial detection filters can be used to superimpose any possible analog spectral detection filter on the image. In this work, we demonstrate three modes of operation, including hyperspectral imagery, and one and two-dimensional imagery using a generalized matched filter for detection of a specific target gas within the scene.

A second-generation long-wave hyperspectral imager based on micro-electro-mechanical systems (MEMS) technology is in development. Spectral and spatial encoding using a MEMS digital micro-mirror device enables fast, multiplexed data acquisition with arbitrary spectral response functions. The imager may be programmed to acquire spectrally selective contrast imagery, replacing more time-consuming hyperspectral data collection. A single-element detector collects encoded data and embedded real-time hardware generates imagery. An internal scanning mechanism enables rapid retrieval of full hyperspectral imagery. The resulting rugged, low-cost sensor will provide chemically specific imagery for applications in gaseous and surface contaminant detection, surveillance, remote sensing, and process control.

A dispersive transform spectral imager named FAROS (FAst Reconfigurable Optical Sensor) has been developed for high frame rate, moderate-to-high resolution hyperspectral imaging. A programmable digital micromirror array (DMA) modulator makes it possible to adjust spectral, temporal and spatial resolution in real time to achieve optimum tradeoff for dynamic monitoring requirements. The system's F/2.8 collection optics produces diffraction-limited images in the mid-wave infrared (MWIR) spectral region. The optical system is based on a proprietary dual-pass Offner configuration with a single spherical mirror and a confocal spherical diffraction grating. FAROS fulfills two functions simultaneously: one output produces two-dimensional polychromatic imagery at the full focal plane array (FPA) frame rate for fast object acquisition and tracking, while the other output operates in parallel and produces variable-resolution spectral images via Hadamard transform encoding to assist in object discrimination and classification. The current version of the FAROS spectral imager is a multispectral technology demonstrator that operates in the MWIR with a 320 x 256 pixel InSb FPA running at 478 frames per second resulting in time resolution of several tens of milliseconds per hypercube. The instrument has been tested by monitoring small-scale rocket engine firings in outdoor environments. The instrument has no macro-scale moving parts, and conforms to a robust, small-volume and lightweight package, suitable for integration with small surveillance vehicles. The technology is also applicable to multispectral/hyperspectral imaging applications in diverse areas such as atmospheric contamination monitoring, agriculture, process control, and biomedical imaging, and can be adapted for use in any spectral domain from the ultraviolet (UV) to the LWIR region.

We describe an in-scene method for VNIR-SWIR atmospheric correction for multi- and hyperspectral imagery, dubbed QUAC (QUick Atmospheric Correction). It determines the atmospheric compensation parameters directly from the information contained within the scene using the observed pixel spectra. The approach is based on the empirical finding that the mean spectrum of a collection of diverse material spectra, such as the endmember spectra in a scene, is essentially invariant from scene to scene. It allows the retrieval of reasonably accurate reflectance spectra even when the sensor does not have a proper radiometric or wavelength calibration, or when the solar illumination intensity is unknown. The computational speed of the atmospheric correction method is significantly faster than for the first-principles methods, making it potentially suitable for real-time applications. QUAC is applied to atmospherically correction of example AVIRIS and HyMap data sets. Comparisons to the physics-based FLAASH code are shown.

The quick atmospheric correction (QUAC) code performs atmospheric correction on multi-and hyperspectral imagery spanning all or part of the visible and near infrared-short wave infrared spectral range, similar to 400 - 2500 nm. It utilizes an in-scene approach, requiring only approximate specification of sensor band locations (i.e., central wavelengths) and their radiometric calibration; no additional metadata is required. Because QUAC does not involve first principles radiative-transfer calculations, it is significantly faster than physics-based methods; however, it is also more approximate. We present a detailed description of the QUAC algorithm, highlighting recent accuracy improvements. Example results for several multi-and hyperspectral data sets are presented, and comparisons are made to more rigorous correction approaches. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.11.111719]

Dispersive transform spectral imagers with both one- and two-dimensional spatial coverage have been demonstrated and characterized for applications in remote sensing, target classification and process monitoring. Programmable spatial light modulators make it possible to adjust spectral, temporal and spatial resolution in real time, as well as implement detection algorithms directly in the digitally controlled sensor hardware. Operating parameters can be optimized in real time, in order to capture changing background and target evolution. Preliminary results are presented for short wave, mid-wave, and long-wave infrared sensors that demonstrate the spatial and spectral versatility and rapid adaptability of this new sensor technology.

An innovative passive standoff system for the detection of chemical/biological agents is described. The spectral, temporal and spatial resolution of the data collected are all adjustable in real time, making it possible to keep the tradeoff between the sensor operating parameters at optimum at all times. The instrument contains no macro-scale moving parts and is therefore an excellent candidate for the development of a robust, compact, lightweight and low-power-consumption sensor. The design can also serve as a basis for a wide variety of spectral instruments operating in the visible, NIR, MWIR, and LWIR to be used for surveillance, process control, and biomedical applications.

Passive optical probes and high-resolution emission spectroscopy are used to provide a general-purpose real-time temperature and chemical species sensing capability. Probes can be inserted in the combustor, at the turbine inlet, in the augmenter, or at the engine exit with application as an engine development diagnostic tool that provides spatially resolved measurements of the key combustion parameters: temperature, CO concentration, and H2O concentration Multiple probes are arrayed to collect the emitted infrared radiation over different views of the hot gas path. Line-of-sight averaged concentrations and temperatures are determined by spectral analysis of the emitted radiation along each line of sight (LOS). Spatial profiles may also be determined by simultaneous analysis of overlapping lines of sight. The collected infrared spectra contain optically thin and optically thick features that reflect the effects of emission and absorption within the combustion region. The known spectral structure of the component spectra can be used for the automated interpretation of the observed radiance spectra in terms of concentrations and temperatures along the line of sight, and in specific volume elements of overlapping lines of sight. In this work, we present measurements of atmosphericpressure flames and high-pressure combustors and describe the formalism for fitting the observed spectra to a basis of simulated spectra to extract estimates of concentrations and temperatures. The spectral basis is constructed using a multilayer radiation transport model, in which each line-of-sight or measurement volume is divided into segments of uniform concentration and temperature. The observed radiance emanating from each segment is calculated as a function of the local physical variables. The collection of observed data, which contains a highly structured emission spectrum over each line of sight, is fit to the spectral basis to extract line-ofsight averaged physical properties, or in the case of spatial reconstruction, volume-averaged properties for each of the overlap regions.