A lightweight, high-resolution spectral imager was developed for aerial surveys of vegetative traits using small drones. The sensor has the potential to rapidly map vegetative type, health, and function over large areas, and revisit the same area to measure seasonal changes in vegetative mass, water uptake, and other traits. It will be invaluable for the growing field of precision agriculture and for ecosystem research. The key benefit, compared to other existing hyperspectral sensors, is the extended spectral range, from the visible into the short-wave infrared, which enables measurement of vegetative features that cannot be accurately measured with existing visible sensors. In Phase II, we developed a small, low-weight, hyperspectral imaging system for UASs based on a high-performance solid-core spectrograph and robust processing algorithms that produce calibrated vegetation trait products. The key innovation was the design and fabrication of solid-block spectrometer machined from a transparent crystal that has an extended spectral range from the visible to the short-wave-infrared (0.38-2.45 microns). It is coupled with a wide-field of view telescope and extended-range camera to produce hyperspectral image (2D images in 400 different colors) with extremely high spatial and spectral resolution. The spectrograph is packaged with ancillary electronics, GPS, and inertial navigation, into a small, 5-pound package that attaches to a standard multicopter drone. SSI is teamed with DOE researchers to develop the science behind measuring vegetative traits from the air, concentrating on how spectral traits correlate from the leaf scale to the landscape scale. In Phase II we have demonstrated the flight package and mapping techniques using a surrogate spectrometer with a smaller spectral range. In a follow-on Phase IIA program, we will be flying the extended-range sensor in coordinated field tests to correlate the landscape-scale hyperspectral measurements with ground measurements. The new extended-range sensor will be integrated into a commercial product line aimed at the precision agriculture and mineral exploration industries. It represents a breakthrough in size, weight, and performance that will enable routine application in the growing, but cost-sensitive field of precision agriculture. It will also be sold for ecological research. Large-scale production of the sensor will enable systematic, ecosystem-scale surveys of plant type, plant-health, carbon-uptake, and vegetative mass.

Polarimetric measurements can substantially enhance the ability of both spectrally resolved and single band imagery to detect the proliferation of weapons of mass destruction, providing data for locating and identifying facilities, materials, and processes of undeclared and proliferant nuclear weapons programs worldwide. Unfortunately, models do not exist that efficiently and accurately predict spectral polarized signatures for the materials of interest embedded in complex 3D environments. Having such a model would enable one to test hypotheses and optimize both the enhancement of scene contrast and the signal processing for spectral signature extraction. The Phase I set the groundwork for development of fully validated polarimetric spectral signature and scene simulation models. This has been accomplished 1. by (a) identifying and downloading state-of-the-art surface and atmospheric polarimetric data sources, (b) implementing tools for generating custom polarimetric data, and (c) identifying and requesting US Government funded field measurement data for use in validation; 2. by formulating an approach for upgrading the radiometric spectral signature model MODTRAN to generate polarimetric intensities through (a) ingestion of the polarimetric data, (b) polarimetric vectorization of existing MODTRAN modules, and (c) integration of a newly developed algorithm for computing polarimetric multiple scattering contributions; 3. by generating an initial polarimetric model that demonstrates calculation of polarimetric solar and lunar single scatter intensities arising from the interaction of incoming irradiances with molecules and aerosols; 4. by developing a design and implementation plan to (a) automate polarimetric scene construction and (b) efficiently sample polarimetric scattering and reflection events, for use in a to be developed polarimetric version of the existing first-principles synthetic scene simulation model, MCScene; and 5. by planning a validation field measurement program in collaboration with the Remote Sensing and Exploitation group at Sandia National Laboratories (SNL) in which data from their ongoing polarimetric field and laboratory measurement program will be shared and, to the extent allowed, tailored for model validation in exchange for model predictions under conditions and for geometries outside of their measurement domain.

A new, compact and portable spectral imaging camera, employing a MEMs-based encoded imaging approach, has been built and demonstrated for detection of hazardous contaminants including gaseous effluents and solid-liquid residues on surfaces. The camera is called the Thermal infrared Reconfigurable Analysis Camera for Effluents and Residues (TRACER). TRACER operates in the long wave infrared and has the potential to detect a wide variety of materials with characteristic spectral signatures in that region. The 30 lb. camera is tripod mounted and battery powered. A touch screen control panel provides a simple user interface for most operations. The MEMS spatial light modulator is a Texas Instruments Digital Microarray Array with custom electronics and firmware control. Simultaneous 1D-spatial and 1Dspectral dimensions are collected, with the second spatial dimension obtained by scanning the internal spectrometer slit. The sensor can be configured to collect data in several modes including full hyperspectral imagery using Hadamard multiplexing, panchromatic thermal imagery, and chemical-specific contrast imagery, switched with simple user commands. Matched filters and other analog filters can be generated internally on-the-fly and applied in hardware, substantially reducing detection time and improving SNR over HSI software processing, while reducing storage requirements. Results of preliminary instrument evaluation and measurements of flame exhaust are presented.

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.

Remotely sensed spectral imagery of the earth's surface can be used to fullest advantage when the influence of the atmosphere has been removed and the measurements are reduced to units of reflectance. Here, we provide a comprehensive summary of the latest version of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes atmospheric correction algorithm. We also report some new code improvements for speed and accuracy. These include the re-working of the original algorithm in C-language code parallelized with message passing interface and containing a new radiative transfer look-up table option, which replaces executions of the MODTRAN (R) model. With computation times now as low as 10 s per image per computer processor, automated, real-time, on-board atmospheric correction of hyper- and multi-spectral imagery is within reach. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.11.111707]

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.

The MODTRAN5 radiation transport (RT) model is a major advancement over earlier versions of the MODTRAN atmospheric transmittance and radiance model. New model features include (1) finer spectral resolution via the Spectrally Enhanced Resolution MODTRAN (SERTRAN) molecular band model, (2) a fully coupled treatment of auxiliary molecular species, and (3) a rapid, high fidelity multiple scattering (MS) option. The finer spectral resolution improves model accuracy especially in the mid- and long-wave infrared atmospheric windows; the auxiliary species option permits the addition of any or all of the suite of HITRAN molecular line species, along with default and user-defined profile specification; and the MS option makes feasible the calculation of Vis-NIR databases that include high-fidelity scattered radiances. Validations of the new band model algorithms against line-by-line (LBL) codes have proven successful.

A new sensor-specific correlated-k (c-k) ultra-fast radiative transfer (RT) formalism, kURT, has been designed for fast broad-bandpass scene simulations from UV-visible to LWIR wavelengths. A higher resolution RT code (1 cm-1 MODTRAN) has been adapted to output 1 cm-1 correlated-k parameters for ozone, water, and the combined uniformly mixed species on a pressure-temperature grid, which are merged to form a compact c-k set incorporating the sensor bandpass response function. The compact set is used to compute bandpass transmittance and radiance in near-real time. Scattering parameters (molecular Rayleigh, clouds and aerosols), blackbody and solar functions are cast as compact k-dependent source terms and used in the radiance computations. Preliminary transmittance results for 3-5 and 8-12 micron bandpasses and visible-MWIR sensors yield results within 2% of a 1 cm-1 MODTRAN calculation with a two-orders-of-magnitude computational savings. Applications include near-earth broadband propagation and extinction calculations for target detection and recognition, mid-range tracking, and search and rescue operations from ground and low altitude aircraft.

Speckle imaging techniques have been shown to mitigate atmospheric-resolution limits, allowing near-diffraction-limited images to be reconstructed. Few images of extended objects reconstructed by use of these techniques have been published, and most of these results are for relatively bright objects. We present image reconstructions of an orbiting Molniya 3 spacecraft from data collected by use of a 2.3-m ground-based telescope. The apparent brightness of the satellite was 15th visual magnitude. Power-spectrum and bispectrum speckle imaging techniques are used prior to image reconstruction to ameliorate atmospheric blurring. We discuss how these images, although poorly resolved, can be used to provide information on the satellite's functional status. It is shown that our previously published optimal algorithms produce a higher-quality image than do conventional speckle imaging methods.