This PDF file contains the front matter associated with SPIE Proceedings Volume 8040, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

A composite signature is a group of signatures that are related in such a way to more completely or further define a target or operational endeavor at a higher fidelity. This paper explores the merits of using composite signatures, in lieu of waiting for opportunities for the more elusive diagnostic signatures, to satisfy key essential elements of information Keywords: signature, composite signature, civil disaster (EEI) associated with civil disaster-related problems. It discusses efforts to refine composite signature development methodology and quantify the relative value of composite vs. diagnostic signatures. The objectives are to: 1) investigate and develop innovative composite signatures associated with civil disasters, including physical, chemical and pattern/behavioral; 2) explore the feasibility of collecting representative composite signatures using current and emerging intelligence, surveillance, and reconnaissance (ISR) collection architectures leveraging civilian and commercial architectures; and 3) collaborate extensively with scientists and engineers from U.S. government organizations and laboratories, the defense industry, and academic institutions.

The method of spectral dynamics analysis (SDA-method) is used for obtaining the2D THz signature of drugs. This signature is used for the detection and identification of drugs with similar Fourier spectra by transmitted THz signal. We discuss the efficiency of SDA method for the identification problem of pure methamphetamine (MA), methylenedioxyamphetamine (MDA), 3, 4-methylenedioxymethamphetamine (MDMA) and Ketamine.

The National Institute of Standards and Technology (NIST) Speaker Recognition Evaluations (SRE) are an ongoing series of projects conducted by NIST. In the NIST SRE, speaker detection performance is measured using a detection cost function, which is defined as a weighted sum of probabilities of type I error and type II error. The sampling variability can result in measurement uncertainties of the detection cost function. Hence, while evaluating and comparing the performances of speaker recognition systems, the uncertainties of measures must be taken into account. In this article, the uncertainties of detection cost functions in terms of standard errors (SE) and confidence intervals are computed using the nonparametric two-sample bootstrap methods based on our extensive bootstrap variability studies on large datasets conducted before. The data independence is assumed because the bootstrap results of SEs matched very well with the analytical results of SEs using the Mann-Whitney statistic for independent and identically distributed samples if the metric of area under a receiver operating characteristic curve is employed. Examples are provided.

Recent advances in the design, development, and deployment of U.S. Army Research Laboratory's (ARL) Multimodal Signature Database (MMSDB) create a state-of-the-art database system with Web-based access through a Web interface designed specifically for research and development. Tens of thousands of signatures are currently available for researchers to support their algorithm development and refinement for sensors and other security systems. Each dataset is stored in (Hierarchical Data Format 5 (HDF5) format for easy modeling and storing of signatures and archived sensor data, ground truth, calibration information, algorithms, and other documentation. Archived HDF5 formatted data provides the basis for computational interoperability across a variety of tools including MATLAB, Octave, and Python. The database has a Web-based front-end with public and restricted access interfaces, along with 24/7 availability and support. This paper describes the overall design of the system, and the recent enhancements and future vision, including the ability for researchers to share algorithms, data, and documentation in the cloud, and providing an ability to run algorithms and software for testing and evaluation purposes remotely across multiple domains and computational tools. The paper will also describe in detail the HDF5 format for several multimodal sensor types.

For several years, NASA has been pursuing demonstrations and development of coherent uplink arraying techniques for the next generation space communications and planetary radar systems. In addition radio science experiments would benefit with a 1000 times increase in signal to noise over current systems. I shall describe the three methods of uplink arraying NASA has pursued, all successful, and share the vision for going forward from laboratory demonstrations to the proposed implementation and deployment of a dedicated multi-purpose facility to infuse an amalgam of these methods into a system that enhances NASA's missions.

Recent successes in detecting specific materials with hyperspectral sensing systems belie the challenging problems that loom. Easy targets, spectrally distinct from clutter, challenge neither detection algorithms, nor the methods used to translate laboratory signatures into field spectra. The full promise of wide area autonomous detection with hyperspectral systems will not be met using rudimentary algorithms, such as the linear matched filter or the ACE algorithm. Nor will signature translation methods that produce a single radiance estimate suffice. This paper suggests a new methodology for addressing future challenges, along with signature characterization protocols that would enable advanced detection capabilities.

The optical performances of the Fiber Bragg Gratings (FBG) all-optical switches are studied under the case of the cross-phase modulation (XPM). The expressions of the switching power threshold in the different detuning range are given. The influence of parameter about different detuning and couple ratio to the threshold of switching power and extinction ratio of devices is also studied.

Several hyperspectral imaging (HSI) systems have been developed with the intent of utilizing spectral diversity in a scene to characterize the background and identify targets of interest. With the increased spectral information, targets much smaller than the spatial extent of a pixel (e.g., pedestrians) can be detected and identified. However, several challenges arise when employing HSI systems for use in the detecting and tracking of pedestrians. Most notably, the signature for the target of interest may or may not be immediately available to the system. The successful detection of sub-pixel targets with any degree of accuracy relies on a priori knowledge of the spectral signature for the targets of interest. Previous work has shown that even if a spectral signature for a pedestrian was acquired at the time of detection, as the pedestrian moved through a cluttered environment its spectral signature changes. This work extends the understanding of the induced spectral variation in human spectral signatures in cluttered environments. The goal of this work was to isolate the spectral reflectivity of highly transmissive targets independent of the background. Using a doubling method, the effects of reflective backing materials on the signature of a thin fabric is presented. Also, an issue with tracking a pedestrian from full illumination into the shadow is considered. Reflectance factor signatures were measured using target reflectivity measured both in the lab and in the field to assess spectral variability and detectability.

Material detection from multi-spectral imagery is critical to numerous geospatial applications. However, given the limited number of channels from various air and space-borne imaging sensors, coupled with varying illumination conditions, material-specific detection rules tend to generate large numbers of false positives. This paper will describe a novel approach that uses various band ratios (for example, [Blue + Green]/Red) to identify targets-of-interest, regardless of the illumination conditions and position of the sensor relative to the target. The approach uses a physics-based spectral model to estimate the observed channel-weighted radiance based on solar irradiance, atmospheric transmission, reflectivity of the target-of-interest and the spectral weighting functions of the sensor's channels. The observed channelweighted radiance is then converted to the expected channel pixel value by the channel-specific conversion factor. With each channel's pixel values estimated, the algorithm goes through a process to find which band ratio values show the least amount of variance, despite varying irradiance spectra and atmospheric absorption. The band ratios with the least amount of variance are then used to identify the target-of-interest in an image file. To determine the expected false alarm rate, the same band ratios are evaluated against a library of background materials using the same calculation method for determining the target-of-interest's channel pixel values. Testing of this approach against ground-truth imagery, with as few as four channels, has shown a high rate of success in identifying targets-of-interest, while maintaining low false alarm rates.

We conducted an investigation of accuracy and applicability of linear and non-linear mixture models to analyze the spectra of binary mixtures of particulates as they apply to hyperspectral remote sensing. The goal of the spectral analysis is to estimate the abundance of each constituent in the binary mixture in terms of the mass of each constituent. All of the data analyzed for this were collected under controlled laboratory conditions using particulate materials that were carefully sifted to limit the particle size distributions. Quantification of intimate mixtures may not be practical in remote sensing due to the requirement that one needs to have detailed knowledge of the materials being observed and the manner in which they are mixed. However, when the particle sizes and mass densities are similar to one another, one can get a reasonable estimate of the mass fractions of a mixture using a simple linear mixture model.

We reiterate the fact that the apparent emissivity of a solid surface can depend on not only the composition and particle size distribution comprising the surface but also on view-angle relative to the bulk surface geometry. We report on experiments measuring the longwave infrared emissivity of quartz sand samples sorted by particle size and observed at a series of view angles up to 60° away from the normal to the bulk sample surface. We show that particle-size and view-angle effects on the apparent emissivity of our quartz samples can mimic each other. In circumstances where significantly off-normal view-angles are unavoidable and characterizing surface qualities are desired, these two effects could be confused. We discuss the existing explanations for these effects. We argue that the view-angle emissivity dependence is intrinsically a bulk geometric effect, not due to a change in apparent particle-size (via coarse grains obscuring finer ones at larger view-angles). We summarize the predominant qualitative explanations of the particle-size effects and review the literature comparing quantitative models and observations. We argue that the existing quantitative models are inadequate for explaining the observations, pointing to a need for further work in this area.

Measurements in dry desert soils have shown significant complex resistivity (or impedivity) variations across the frequency range from 1 kHz to 1 MHz. The impedivity of various soils are measured in-situ in field experiments using a custom apparatus, consisting of a probe head and accompanying custom electronics. Four galvanic electrodes are fixed in the probe head, and arranged in a Wenner array, such that the geometric factor is 1.00 m. In this way, impedance measurements (in Ω) are easily converted to estimates of impedivity (in Ω · m). Field measurements made in-situ are important for obtaining accurate results, because impedance measurements typically change value significantly once soil samples are extracted from their natural environment. These changes are due to changes in the grain boundaries, as well as changes in moisture, temperature, etc. Soil impedivity signatures collected on a variety of soils in the south west region of the USA over the frequency band up to 1 MHz are presented.

The Deepwater Horizon explosion and subsequent sinking produced the largest oil spill in U.S. history. One of the most prominent portions of the response is mapping the extent to which oil has reached thousands of miles of shoreline. The most common method of detecting oil remains visual spotting from airframes, supplemented by panchromatic / multispectral aerial photography and satellite imagery. While this imagery provides a synoptic view, it is often ambiguous in its ability to discriminate water from hydrocarbon materials. By employing spectral libraries for material identification and discrimination, imaging spectroscopy supplements traditional imaging techniques by providing specific criteria for more accurate petroleum detection and discrimination from water on terrestrial backgrounds. This paper applies a new hydrocarbon-substrate spectral library to SpecTIR HST-3 airborne imaging spectroscopy data from the Hurricane Katrina disaster in 2005. Using common material identification algorithms, this preliminary analysis demonstrates the applicability and limitations of hyperspectral data to petroleum/water discrimination in certain conditions. The current work is also the first application of the petroleum-substrate library to imaging spectroscopy data and shows potential for monitoring long term impacts of Deepwater Horizon.

We address the automatic detection of Ambush weapons such as rocket propelled grenades (RPGs) from range data which might be derived from multiple camera stereo with textured illumination or by other means. We describe our initial work in a new project involving the efficient acquisition of 3D scene data as well as discrete point invariant techniques to perform real time search for threats to a convoy. The shapes of the jump boundaries in the scene are exploited in this paper, rather than on-surface points, due to the large error typical of depth measurement at long range and the relatively high resolution obtainable in the transverse direction. We describe examples of the generation of a novel range-scaled chain code for detecting and matching jump boundaries.

Ladar technology has long since established its advantages as a reliable method for automated Terrain Mapping. One still remaining important problem of this methodology though happens at data processing time. Ladars generate huge amounts of data referred to as 'point clouds'. The very first task in data processing consists of segmenting the terrain image between ground and non-ground data points. The standard processing methods all rely on some slope analysis technique. At the present moment, all these techniques still require interactive evaluation and manual editing of the results. In this work, Ladar polarization is used to discriminate between solid targets by using their polarization signatures. The addition of this feature, over and above range and intensity, could greatly help in the process wherein ground and nonground points are to be separated. Linear and circular polarizations measurements were performed on different specimens in various conditions and at various wavelengths. The results presented herein are a validation of the fact that typical solid targets show a response to the Ladar sensor which conforms to the behavior predicted by the most recent polarimetric BDRF theories. Hence, their polarization signature is expected to be repeatable. The results presented herein also show that, to the extent that more than one wavelength is used, solid targets can be discriminated against each other by the use of their polarization signatures.

The paper presents reflectance characteristics of plants. The objects of the research were the selected plants, taking the various levels of organization and structure into consideration, as well as the state of plant health and growth. Reflectance spectrum was analyzed in the range of wavelengths from 0,2 to 2,5 μm. The values of reflectance for three wavelengths (λ₁=850 nm, λ₂=905 nm, λ₃=1550 nm) were analyzed with the particular emphasis. The sample tests were performed immediately after biological material taking and in the several 24-hour time intervals. The time intervals enabled the process of plants wilting and drying. The reflectance measurements were repeated until the moment of plant complete dried out. All measurements were performed with the use of the spectrometer Lambda 900 (Perkin Elmer) equipped with the 150 mm integrating sphere PELA1001 dedicated for the measurements of the hemispherical reflectance both of diffuse and specular type. On the basis of the obtained results one calculated the values of signal ratios for the three selected wavelengths: 850/1550nm, 905/1550nm, and 850/905nm. The collected spectra and reflectance characteristics enabled the analyses of both results similarities and differences, which enabled the determination of the reflectance changes tendency associated with the typical processes occurring in plants. The analyses of plants reflectance characteristics were made for the use of the laser system for identification of terrain elements and their physico-chemical properties.