Fourier transform infrared spectroscopy is a standard technique for remote detection of gaseous vapors. However, as
algorithms mature and hyperspectral imaging in the longwave infrared becomes more prominent in ground based
applications it is important to determine optimum parameters for detection due to potentially high data rates. One
parameter, spectral resolution, is of particular interest because 1) it can be easily changed and 2) it has significant effect
on the data rate. The following presents a mathematical foundation for determining the spectral resolution for vapor
detection in the presence of atmospheric interferants such as water vapor and ozone. Results are validated using real-world
long wave infrared hyperspectral data of several open air chemical simulant releases.
Since this is the tenth Chemical and Biological Sensing Conference, it is timely to reflect on
progress in this field. We present a perspective on biological standoff detection from the point of view of past
and current programs at the Johns Hopkins University Applied Physics Laboratory. Topics will include our
role in field testing, laboratory measurements and system modeling. We will also review the APL program
in optical property determination of biological aerosols. Many challenges have been overcome and many
lessons learned over the years that are worth reporting.
The complexity of biological agents can make it difficult to identify the important factors impacting
scattering characteristics among variables such as size, shape, internal structure and biochemical composition, particle
aggregation, and sample additives. This difficulty is exacerbated by the environmentally interactive nature of
biological organisms. In particular, bacterial spores equilibrate with environmental humidity by absorption/desorption
of water which can affect both the complex refractive index and the size/shape distributions of particles - two factors
upon which scattering characteristics depend critically. Therefore accurate analysis of experimental data for
determination of refractive index must take account of particle water content. First, spectral transmission
measurements to determine visible refractive index done on suspensions of bacterial spores must account for water (or
other solvent) uptake. Second, realistic calculations of aerosol scattering cross sections should consider effects of
atmospheric humidity on particle water content, size and shape. In this work we demonstrate a method for determining
refractive index of bacterial spores bacillus atropheus (BG), bacillus thuringiensis (BT) and bacillus anthracis Sterne
(BAs) which accounts for these effects. Visible index is found from transmission measurements on aqueous and
DMSO suspensions of particles, using an anomalous diffraction approximation. A simplified version of the anomalous
diffraction theory is used to eliminate the need for knowledge of particle size. Results using this approach indicate the
technique can be useful in determining the visible refractive index of particles when size and shape distributions are
not well known but fall within the region of validity of anomalous dispersion theory.
Long-wave infrared hyperspectral sensors provide the ability to detect gas plumes at stand-off distances. A number of
detection algorithms have been developed for such applications, but in situations where the gas is released in a complex
background and is at air temperature, these detectors can generate a considerable amount of false alarms. To make
matters more difficult, the gas tends to have non-uniform concentrations throughout the plume making it spatially similar
to the false alarms. Simple post-processing using median filters can remove a number of the false alarms, but at the cost
of removing a significant amount of the gas plume as well. We approach the problem using an adaptive subpixel detector
and morphological processing techniques. The adaptive subpixel detection algorithm is able to detect the gas plume
against the complex background. We then use morphological processing techniques to isolate the gas plume while
simultaneously rejecting nearly all false alarms. Results will be demonstrated on a set of ground-based long-wave
infrared hyperspectral image sequences.
Aerosol backscatter and extinction cross-sections are required to model and evaluate the performance of
both active and passive detection systems. A method has been developed that begins with laboratory
measurements of thin films and suspensions of biological material to obtain the complex index refraction of
the biological material from the UV to the LWIR. Using that result with particle size distribution and shape
information as inputs to T-matrix or discrete dipole approximation (DDA) calculations yields the extinction
cross-section and backscatter cross section as a function of wavelength. These are important inputs to the
In a continuing effort to provide validated optical cross-sections, measurements have been made
on a number of high purity biological species in the laboratory as well as measurements of material
released at recent field tests. The resulting observed differences between laboratory and field
measurements aid in distinguishing between intrinsic and extrinsic effects, which can affect the
characteristic signatures of important biological aerosols. A variety of biological and test aerosols are
examined, including Bacillus atrophaeus (BG), and Erwina, ovalbumin, silica and polystyrene.
Optical cross-sections of biological warfare simulants, killed agents, and live agents are needed to assess the
standoff detection performance of active lidar and passive FTIR systems. To aid in this investigation, Johns Hopkins
University Applied Physics Laboratory (JHU/APL) has developed a technique to determine the index of refraction of
biological materials in the visible region using a combination of transmission measurements and anomalous diffraction
theory (ADT). The spectral measurements using a dual beam grating spectrometer provide a basis for calculating the
optical cross section of suspended particles. ADT is then used to convert the cross section result into index of refraction.
A summary of this procedure is described along with the results for silica microspheres and Bacillus globijii (BG). A
comparison of these results to published data is also presented.
Calculation of scattering properties of biological materials has classically been addressed using numerical calculations
based on T-matrix theory. These calculations use bulk optical properties, particle size distribution, and a limited selection
of shape descriptors to calculate the resulting aerosol properties. However, the most applicable shape available in T-matrix
codes, the spheroid, is not the best descriptor of most biological materials. Based on imagery of the spores of
Bacillus atrophaeus and Bacillus anthracis, capsule and egg shapes are mathematically described and programmed into
the Amsterdam Discrete Dipole Approximation (ADDA). Spectrally dependent cross sections and depolarization ratios
are calculated and a comparison made to spheroidal shapes of equivalent sizes.
High optical quality polycrystalline yttrium aluminum garnet (YAG) is now available. The optical
properties of pure polycrystalline YAG and 1% Nd doped polycrystalline YAG are reported from the
midwave infrared to the visible. The absorption and scatter properties are represented in terms of standard
The FIRST, a commercial hyperspectral imager developed by Telops, features high sensitivity in a
compact and robust package. This sensor provides hypercubes of spectral radiance of up to 320x256
pixels at 0.35mrad spatial resolution over the 8 - 12 &mgr;m spectral range at user selectable spectral
resolutions of up to 0.25 cm-1. The measurements are converted into "chemical maps" by the use of
powerful algorithms using both spatial and spectral information. The FIRST has been used at several field
tests for the standoff detection and identification of chemicals. During these tests, the sensor is usually
operated at 4 cm-1 of spectral resolution and the image size is tailored according to the dissemination.
Algorithms based on a combination of clutter-matched filters and spectral angle mapper have been
developed and used to process the measured data. The algorithms combine sub-band selection to
minimize the correlation between the spectral signatures in the library and careful selection of the
thresholds to reduce the level of false alarms. The output of the algorithms is the image of the clouds
superimposed on the broadband thermal image. JHU/APL has developed a processing approach that
adapts to different backgrounds, yields low probability of false alarm, and performs well in the presence
of "hot" pixels. The algorithm combines background/noise suppression techniques, spectral detection
techniques, such as the spectral angle mapper and the matched filter, and automatic adaptive threshold
techniques. This paper will present the successful standoff detection and identification of various
chemical compounds using a variety of field measurements. Images of chemical disseminations will be
presented, with some of them including mixtures of 2 different chemicals.
In developing algorithms for remote sensing of chemical and biological warfare agents, it is imperative to have
a good understanding of the background radiance signal and environmental characteristics that influence detection.
Factors such as thermal contrast, interferent atmospheric constituents, spatial clutter, and temporal variations should all
be investigated for both the development and performance modeling of field sensors. To aid in the investigation of these
topics as well as to provide data for current simulation tools, JHU/APL has constructed an automated data collection
suite capable of simultaneous radiometric measurements in the longwave IR (8μm - 12μm) and midwave IR (3μm -
5μm) while also measuring a host of relevant atmospheric parameters. The primary radiometric sensor, an ABB Bomem
MR304, is mounted on a pan/tilt system that is used to scan regions of interest while periodically generating calibration
data. This paper describes the system design requirements, specifications of the individual components, and the overall
system performance. In addition, data from field exercises are presented.
There is wide variability in measured optical cross-sections for bio-aerosols. This variability may be due to a variety of causes, such as multiple scatter, particle agglomeration, etc. There are wide variations in numerically predicted cross-sections as well. In this case, the variability may be due to uncertainties in particle size distributions and complex refractive indices. Another source of variability in the numerical predictions that places them at odds with measured cross-sections is unrealistic assumptions about shape. For example, it is well known that spheres of a given volume are maximally efficient in backscatter. Thus, such an assumption produces unrealistically high backscatter cross-section estimates.
In an attempt to elucidate some of the variability in measured and calculated data, we explore the sensitivity to the various parameters affecting these cross-sections. We explore the effects from the near into the far IR, of variations in particle size distribution, refractive index, and shape. Refractive index data are from the literature as well as our own laboratory. Numerical calculations are made using T-matrix algorithms for randomly oriented particles. Calculated results are compared with experimental measurements from the literature and with measurements in our own laboratory.
Results of this sensitivity study are important in any remote measurement system designed to discriminate between particular bio-aerosol species and ambient aerosols.
In a continuing series of experiments designed to determine the spectral extinction cross-section of bacterial aerosols, a White cell transmissometer was constructed to obtain stable, long path length measurements. Laser transmittance at different aerosol concentrations allows calculation of the extinction cross-sections. Using three lasers, a HeNe at 543 nm, a diode pumped solid state at 1.064 μm, and a fiber laser at 1.558 μm, the data on the spectral cross section of Bacillus globigi (BG) was extended into the NIR. The extinction cross-section was estimated to be 2.58 x 10-8 cm2 at 543 nm wavelength during the 2003 measurements, which is consistent with previous measurements at this wavelength. In the NIR, the cross section of BG was determined to be 2.71 x 10-8 cm2 and 2.32 x 10-8 cm2 at 1.064 and 1.558 μm, respectively. To validate the measurements, Mie calculations were used to continuously represent the extinction and backscatter cross-sections from the UV to NIR. The efforts described herein are intended to explore the various optical scatter features that may allow discrimination of biological pathogens from naturally occurring aerosol constituents such as pollen, dust, etc.