This PDF file contains the front matter associated with SPIE Proceedings Volume 6756, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Wavelength modulation spectroscopy (WMS) with tunable diode lasers (TDLs) is the preferred technique for gas composition measurement in a growing number of industrial process control applications. Those systems using optical fiber cables or networks to address single or multiple sensing points are of particular interest. However, the conventional approaches suffer from a number of calibration / scaling factor issues which, although addressable, lead to added cost and accumulated errors in the final determination of gas concentration. Such issues are particularly problematic in industrial applications where the pressure may be varying and unknown. The target signal in WMS is an amplitude modulation (AM) component generated by the interaction of frequency modulation (FM) on the laser output with a rotational / vibrational gas absorption line function. However, direct laser amplitude modulation is also present and distorts the recovered target signals again leading to errors. Here we report an alternative approach in which we exploit the phase difference between the laser AM and the FM to provide direct recovery of the absolute gas absorption line function from which both the gas concentration and the pressure may be obtained from the depth and line width respectively. The method is absolute with no need for calibration thus eliminating the difficulties with the conventional approach. In our presentation, we report the basic principles of the technique and its experimental validation through a number of methane gas concentration and pressure measurements.

A promising absorption spectroscopy application for mid-IR lasers is exhaled breath analysis where sensitive, selective, and speedy measurement of small gas phase biomarker molecules can be used to diagnose disease and monitor therapies. Many molecules such as nitric oxide, ethane, formaldehyde, acetaldehyde, acetone, carbonyl sulfide, and carbon disulfide have been connected to diseases or conditions such as asthma, oxidative stress, breast cancer, lung cancer, diabetes, organ transplant rejection, and schizophrenia. Measuring these and other, yet to be discovered, biomarker molecules in exhaled breath with mid-IR lasers offers great potential for improving health care since such tests are non-invasive, real-time, and do not require expensive consumables or chemical reagents. Motivated by these potential benefits, mid-IR laser spectrometers equipped with presently available cryogenically-cooled IV-VI lasers mounted in compact Stirling coolers have been developed for clinical research applications. This paper will begin with a description of the development of mid-IR laser instruments and their use in the largest known exhaled breath clinical study ever performed. It will then shift to a description of recent work on the development of new IV-VI semiconductor quantum well materials and laser fabrication methods that offer the promise of low power consumption (i.e. efficient) continuous wave emission at room temperature. Taken together, the demonstration of compelling clinical applications with large market opportunities and the clear identification of a viable pathway to develop low cost mid-IR laser instrumentation can create a renewed focus for future research and development efforts within the mid-IR materials and devices area.

Pacific Northwest National Laboratory (PNNL) has active programs investigating the optical absorption strengths of several types of molecules including toxic industrial chemicals (TICs), microbiological threats such as bacteria, as well as explosives such as RDX, PETN and TNT. While most of our work has centered on the mid-infrared domain (600 to 6,500 cm-1), more recent work has also included work in the far-infrared, also called the terahertz (THz) region (500 to ~8 cm-1). Using Fourier transform infrared spectroscopy, we have been able to compare the relative, and in some cases absolute, IR/THz cross sections of a number of species in the solid and liquid phases. The relative band strengths of a number of species of interest are discussed in terms of both experimental and computational results.

A portable fluoroquinolone (FQ) analyzer is designed and prototyped based on terbium-sensitized luminescence (TSL). The excitation source is a 327-nm light emitting diode (LED) operated in pulsed mode; and the luminescence signal is detected by a photomultiplier tube (PMT). In comparison to a conventional xenon flashlamp, an LED is small, light, robust, and energy efficient. More importantly, its narrow emission bandwidth and low residual radiation reduce background signal. In pulse mode, an LED operates at a current 1-2 orders of magnitude lower than that of a xenon flashlamp, thus minimizing electromagnetic interference (EMI) to the detector circuitry. The PMT is gated to minimize its response to the light source. These measures lead to reduced background noise in time domain. To overcome pulse-to-pulse variation signal normalization is implemented based on individual pulse energy. Instrument operation and data processing are controlled by a computer running a custom LabVIEW program. Enrofloxacin (ENRO) is used as a model analyte to evaluate instrument performance. The integrated TSL intensity reveals a linear dependence up to 2 ppm. A 1.1-ppb limit of detection (LOD) is achieved with relative standard deviation (RSD) averaged at 5.1%. The background noise corresponds to ~5 ppb. At 19 lbs, this portable analyzer is field deployable for agriculture, environmental and clinical analyses.

A novel fiber optic sensor for simultaneous measurement of temperature and salinity with multiplexed polymer-coated fiber Bragg gratings is demonstrated. It has been found that the polyimide-coated fibre Bragg grating respond to variations of both temperature and salinity while the acrylate-coated fiber Bragg grating is only sensitive to the environmental temperature. The experimental results showed that the temperature and salinity sensitivities of the multiplexed fiber Bragg grating sensor are 0.0102 nm/°C and 0.0038 nm/%S, respectively.

Continuous-Wave Cavity Ring-Down Spectroscopy (CW-CRDS) has now become a field-proven trace gas measurement technique in the industry. With particular emphasis on field data, this paper demonstrates the strong capability of CW-CRDS for trace species detection in such critical applications as H2O analysis in challenging hydride gas matrices, as well as O2 monitoring for ultra-high-purity (UHP) bulk gases.

An efficient standoff biological warfare detection capability could become an important asset for both defence and security communities based on the increasing biological threat and the limits of the presently existing protection systems. Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor prototype based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF). This LIDAR system named SINBAHD monitors the spectrally resolved LIF originating from inelastic interactions with bioaerosols present in atmospheric cells customizable in size and in range. SINBAHD has demonstrated the capability of near real-time detection and classification of bioaerosolized threats at multi-kilometre ranges. In spring 2005, DRDC has initiated the BioSense demonstration project, which combines the SINBAHD technology with a geo-referenced Near InfraRed (NIR) LIDAR cloud mapper. SINBAHD is now being used to acquire more signatures to add in the spectral library and also to optimize and test the new BioSense algorithm strategy. In September 2006, SINBAHD has participated in a two-week trial held at DRDC-Suffield where different open-air wet releases of live and killed bioagent simulants, growth media and obscurants were performed. An autoclave killing procedure was performed on two biological materials (Bacillus subtilis var globigii or BG, and Bacillus thuringiensis or Bt) before being aerosolized, disseminated and spectrally characterized with SINBAHD. The obtained results showed no significant impact of this killing process on their normalised spectral signature in comparison with their live counterparts. Correlation between the detection signals from SINBAHD, an array of slit samplers and a FLuorescent Aerosol Particle Sensor (C-FLAPS) was obtained and SINBAHD's sensitivity could then be estimated. At the 2006 trial, a detection limit of a few tens of Agent Containing Particles per Liter of Air (ACPLA) was obtained for a 15-m thick cloud of live BG located at a range of 400 m.

An imaging open-path Fourier transform infrared (I-OP-FTIR) spectrometer is being developed for real-time three-dimensional cloud profiling. The system employs a single modulator and a novel optical configuration which projects an array of angularly dispersed IR beams, each of which exhibits comparable throughput to a single channel OP-FTIR, to an array of respective retroreflector arrays remotely located at the opposite side of the test grid. The return light from each retroreflector array is imaged onto respective detectors that record the spatially-resolved interferograms which are subsequently transformed and analyzed for molecular content via advanced multicomponent algorithms. The result is a capability to sensitively, quantitatively, and simultaneously measure the molecular absorbance and associated concentration-pathlength of an open release plume over a spatial region. Use of two or more I-OP-FTIR sensors around the perimeter of the release allows for tomographic reconstruction of the concentration map of each molecular species contained in the plume. This approach realizes the high sensitivity of an OP-FTIR spectrometer without adding the expense and logistical difficulties associated with installing a large number of spectrometer units required for the cloud profiling application. In addition, the active spectral measurement supports detection in zero temperature contrast conditions where the plume is the same temperature as the background. A further reduction in cost and weight is achieved through the use of low-cost plastic press molded retroreflector arrays to return the spatially dispersed open path beams.

Measurement of the isotopic composition of atmospheric methane is a valuable tool for understanding the sources and sinks of the global carbon budget. One promising carbon isotope ratio measurement technology is optical spectroscopy using inter-band cascade (IC) lasers. Ongoing development of these light sources has the goal of providing, from a package operating near room temperature, a single mode laser source in the wavelength range of 3 &mgr;m. The spectral features of methane are sufficiently strong at this wavelength that a path length of about 100 m should suffice for measuring 12- and 13-C isotopes in air without pre-concentrating the sample. Experimental IC lasers are described and their use for isotope sensing by wavelength modulation spectroscopy is evaluated.

For hyperspectral imagery, simulated annealing (SA) and greedy modular eigenspaces (GME) have been successfully developed to cluster highly correlated hyperspectral bands into a smaller subset of band modules. This paper introduces a novel band selection technique of combining these two approaches, called the SA and GME band selection (SGBS), for hyperspectral imagery. The SGBS selects sets of non-correlated hyperspectral bands for hyperspectral images based on heuristic and greedy algorithms, utilizes the inherent separability of different classes in hyperspectral images to reduce dimensionality, and further generates a unique clustered eigenspace (CE) feature set effectively. The proposed SGBS features can 1) avoid the bias problems of transforming the information into linear combinations of bands as does the traditional principal components analysis, 2) evince improved discriminatory properties, crucial to subsequent classification compared with conventional band selection techniques, 3) provide a fast procedure to simultaneously select the most significant features by merging SA and GME schemes, and 4) select each band by a simple logical operation, called the CE feature scale uniformity transformation (CE/FSUT), to include different classes into the most common feature modules of the hyperspectral bands. The performance of the proposed SGBS method was evaluated by MODIS/ASTER airborne simulator (MASTER) images for land cover classification during the Pacific Rim II campaign. Encouraging experimental results showed that the proposed SGBS approach is effective and can be used as an alternative to the existing band selection algorithms.

Previous work by the authors has produced statistically based methods for detecting, estimating and classifying aerosol materials in the atmosphere using multiple-wavelength range-resolved CO2 lidar. This work has thus far been limited to the presence of a single aerosol material at a given time within the lidar line-of-sight. Practical implementation requires the ability to detect and discriminate multiple aerosol materials present simultaneously such as smoke and dust in addition to hazardous materials. Treating mixtures of materials necessitates fundamentally different approaches from the single-material case since neither the aerosol backscatter wavelength-dependence nor the concentrations as a function of range are known. Because of this, linear processing cannot resolve the mixture data into its components unambiguously, and non-linear methods must be considered. In this paper we describe an empirical Bayes (EB) approach for resolving mixtures of aerosol into their components. The basic idea of EB is to use the same data to estimate the prior distribution of a set of parameters as that used to estimate the parameters themselves. In our case the concentration and backscatter are the parameters that are estimated with the help of a prior distribution of the backscatter. We implement the EB estimator through the EM (Expectation Maximization) algorithm. The resulting processor is applied to injections of interferent dust into data sets collected by ECBC during JBSDS testing at Dugway Proving Ground, UT in 2006.

The Least Square (LS) approach is one of the most widely used algorithms for target detection in remote sensing images. It has been proven mathematically that the Noise Whitened Least Square (NWLS) can outperform the original version by making the noise distribution independent and identical distributed (i.i.d.). But in order to have good results, the estimation of the noise covariance matrix is very important and still remains a great challenge. Many estimation methods have been proposed in the past. The first type of methods assumes that the signal between neighbor pixels should be similar, so that the difference between neighborhood pixels or the high-frequency signals can be used to represent noise. These includes spatial and frequency domain high-pass filter, neighborhood pixel subtraction. The more practical method is based on the training samples and calculates the covariance matrix between each training sample and its class mean as the noise distribution, which is the within-class scatter matrix in Fisher's Linear Discriminant Analysis. But it is usually not easy to collect enough training samples to yield full rank covariance matrix. In this paper, we adopt the Nonparametric Weighted Feature Extraction (NWFE) to overcome the rank problem and it is also suitable to model the non-Gaussian noise. We have also compared the results with SPOT-5 image scene.

Hyperspectral images collect hundreds of co-registered images of the earth surface with different wavelengths in visible and short-wave inferred region. With such high spectral resolution, many adjacent bands are highly correlated, i.e., they contain a lot redundant information. How to remove unnecessary information from this huge amount of data and preserve all the information is a challenging problem. Principal component analysis (PCA) is one of the widely used algorithms for this problem. It assumes the larger variance contains the most information, so it projects the data into the direction to maximize the variance. Most of the signals will be kept in the first several principal components, and the rest will be considered to be noise and neglected. To further reduce the redundancy, segment PCA is proposed, which first separate the whole spectral bands into blocks and then perform the original PCA in each block individually. Both these two approaches perform well for data compression, but for image classification in its feature space, they did not achieve comparable results. In this study, we adopt the greedy modular subspaces transformation (GMST) to find the optimal feature subspace for the segment PCA. It is expected to provide a comparable classification results with high compression performance.

The Raman vibrational frequencies in the finger print region (700-1600 cm^-1) have been calculated for 2,4- dinitrotoluene, 2,6-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT). The Raman vibrational intensities and frequencies for these molecules have been calculated using B3LYP Density Functional Theory method with 6-311+G** and Sadlejs medium-sized polarized basis sets (Sadlej pVTZ). The normal mode assignments in the finger print region were carried out by Normal Coordinate Analysis, where localized and de-localized coordinates were used to facilitate an accurate description of the vibrational modes. The Raman intensities were calculated from the Raman scattering cross sections using the ab initio calculated Raman scattering activities. Comparison of these intensities using different basis sets indicates that the Sadlej pVTZ basis sets increase the calculated intensities for the NO₂ symmetric stretching and bending frequencies by more than 15 % relative to 6-311+G** basis. The potential energy distribution for the symmetric and asymmetric NO₂ stretches indicates that 2-NO₂ and 6-NO₂ couple strongly in 2,6-DNT and 2,4,6-TNT, while 2-NO₂ and 4-NO₂ groups couple weakly in 2,4- DNT. These findings suggest that the coupling strength of 2-NO₂, 6-NO₂ and 4-NO₂ groups can be used to distinguish between dinitro and trinitro toluenes.

In the recent years, the most country in the word attach importance to the environmental and the protection of environmental doubly. The differential absorption lidar (DIAL)operating in the infrared wavelengths is a powerful standoff sensor for rapid remote detection of chemical emissions. It represents also a powerful technique for pollution monitoring of the atmosphere environment. Whereas, the numerical simulation system of DIAL has been shown that is a powerful tool for system design and performance evaluation and improved performance of system, along with research new information processing algorithm provided with the laboratory environment. In this Paper, a DIAL operating in the infrared(LWIR)numerical simulated system is established. It can simulate both traditional two-wavelength DIAL and multi-wavelength DIAL. It simulates the directional or scanning two operational modes. One can obtain information by it such as gas kind, concentration and distribution and verify the information processing algorithms visually. It can generate the return signals and can calculate their SNR value for various simulated environment and weather and system conditions visually. In the paper, first review laser light atmospheric propagation characteristic and then, the environmental models is ascertained including the effects of the atmosphere attenuates and scatters, the atmospheric turbulence and the roughness target producing reflective speckle and so on. Especially, the DIAL simulated system includes some new information processing algorithms of discriminating target gases and estimating their concentration. By now, the DIAL simulated system combined with this information processing algorithms has not been reported.