Alakai Defense Systems has recently developed what we believe is the first one-handed UV Raman sensor for standoff trace detection of chemicals, which we refer to as Argos. Argos, equipped with increased range and detection capability, is the higher performance version of the lower cost SAFR sensor. And because they are lightweight, both Argos and SAFR can be deployed onto unmanned ground vehicles (UGVs) or unmanned aerial vehicles (UAVs). Data will be presented showing Argos detection performance on residue and trace samples at ranges from 2 m to 15 m. Further, data will be presented from UGV and UAV experiments performed with the SAFR system in warehouse and outdoor applications.
Alakai Defense Systems has recently developed what we believe is the first one-handed UV Raman sensor for standoff trace detection of chemicals, which we refer to as Argos. Argos is the higher performance version of lower cost SAFR sensor, since it has increased range and trace detection capability. Since it is lightweight, Argos can also be deployed on Unmanned Ground Vehicles (UGV’s) or Unmanned Aerial Vehicles (UAVs). Data is presented showing how Argos detection performance is essentially the same as Alakai’s proven trace detection sensor PRIED, however it is ~70% smaller and lighter.
Alakai Defense Systems has developed several standoff ultra-violet (UV) Raman systems over the years to enable detection of hazardous chemicals from a safe distance. These systems have traditionally used classical non-machine-learning-based algorithms, but Alakai together with its partner Systems & Technology Research (STR) are currently developing the Agnostic Machine learning Platform for Spectroscopy (AMPS). AMPS, implemented using PyTorch, automatically creates and optimizes tailored one-dimensional (1D) convolutional neural networks (CNN) when trained on simulated or measured data. Several emerging and novel techniques, including advanced domain adaptation approaches, have been implemented to increase model robustness and minimize training data requirements. While the created models are optimized for a specific modality, AMPS itself is agnostic—it can be used for any spectroscopic modality that produces 1D spectra. AMPS has shown promising results for long-wave infrared (LWIR) reflectance spectroscopy as well as UV and near-infrared (NIR) Raman. This talk will focus on AMPS models created using both simulated UV Raman data as well as measured UV Raman data taken with Alakai’s Portable Raman Improvised Explosives Detection (PRIED) system. Performance between AMPS and Alakai’s legacy algorithms will be compared.
Alakai Defense Systems has recently developed what we believe is the first one-handed UV Raman sensor for standoff detection of chemicals, which we refer to as the Situational Awareness for First Responders (SAFR-1). Alakai is now expanding that product line to offer a higher performance version called SAFR-2 for longer range and trace detection. SAFR-1 detects bulk and residue quantities of material up to a range of 5 m. Since it is lightweight, SAFR can also be deployed on Unmanned Ground Vehicles (UGV’s) or Unmanned Aerial Vehicles (UAVs). SAFR-2 incorporates an Intensified CCD (ICCD) array for more sensitivity and trace detection capability.
Alakai Defense Systems has recently developed what we believe is the first one-handed UV Raman sensor for standoff detection of chemicals, which we refer to as the Situational Awareness for First Responders (SAFR). SAFR detects bulk and residue quantities of material up to a range of 5 m. Since it is lightweight, SAFR can also be deployed on Unmanned Ground Vehicles (UGV’s) or Unmanned Aerial Vehicles (UAVs). A short description of the instrument’s design and performance will be presented.
Alakai Defense Systems will present improvements and data from its DUV Raman system. Specifically, this is an Ultraviolet (UV) Raman microscope for the rapid scanning of fingerprints for the detection of trace explosives. Since this sensor operates in the UV spectrum, it can rapidly scan an area mapping out the results in minutes versus tens of minutes to hours for Near-infrared (NIR) systems. A short description of the instrument and performance is presented.
Alakai Defense Systems has upgraded its short range UV Raman standoff explosive detection sensors called the Portable Raman Improvised Explosive Detection (PRIED) sensor by adding near trace detection capability. The PRIED sensor is a standoff detection sensor that works at ranges of 1-10m for a wide variety of explosives (50m for some selected chemicals). Recent improvements have focused on expanding PRIED’s capabilities to include near-trace detection of explosives at 1-2m range on fluorescent substrates. Data will be presented showing this new capability along with a brief description of the design upgrades
Alakai Defense Systems has created two new short range UV Raman standoff explosive detection sensors. These are called the Critical Infrastructure Protection System (CIPS) and Portable Raman Improvised Explosive Detection System (PRIED) and work at standoff ranges of 10cm and 1-10m respectively. Both these systems are designed to detect neartrace quantities of explosives and Homemade Explosives. A short description of the instruments, design trades, and CONOPS of each design is presented. Data includes a wide variety of explosives, precursors, TIC/TIM’s, narcotics, and CWA simulants
Alakai Defense Systems has created a standoff explosive detection sensor called the Check Point Explosives Detection
System for use at military check points. The system is designed to find trace level explosive residues from a standoff
distance to thwart the transport and use of illegal homemade explosives, precursors and related contraband. Because of
its standoff nature, this instrument could offer benefits to those searching for explosives, since it removes the searcher
from harm's way if a detonation occurs. A short description of the instrument, improvements to the system over the past
year, and a brief overview of recent testing are presented here.
In order to stop the transportation of materials used for IED manufacture, a standoff checkpoint explosives detection
system (CPEDS) has recently been fabricated. The system incorporates multi-wavelength Raman spectroscopy and laser
induced breakdown spectroscopy (LIBS) modalities with a LIBS enhancement technique called TEPS to be added later
into a single unit for trace detection of explosives at military checkpoints. Newly developed spectrometers and other
required sensors all integrated with a custom graphical user interface for producing simplified, real-time detection results
are also included in the system. All equipment is housed in a military ruggedized shelter for potential deployment intheater
for signature collection. Laboratory and performance data, as well as the construction of the CPEDS system and
its potential deployment capabilities, will be presented in the current work.
Recent progress has been made on an explosive laser standoff detection system called TREDS-2 constructed from COTS
components. The TREDS-2 system utilizes combination of Laser Induced Breakdown (LIBS), Townsend Effect Plasma
Spectroscopy (TEPS) and Raman spectroscopy techniques with chemometric algorithms to detect hazardous materials.
Extension of the detection capability of the TREDS-2 system on the real-time point detection of chemical, biological,
radioactive, and nuclear threats has been tested and presented in this report.
System performance of surface detection of a variety of CBRNE materials is shown. An overview of improvements to
the explosives detection capabilities is given first. Challenges to sensing some specific CBRN threats are then discussed,
along with the initial testing of TREDS-2 on CBRN surrogates on a limited number of surfaces. Signal processing using
chemometric algorithms are shown as a demonstration of the system's capabilities. A path forward for using the specific
technologies is also provided, as well as a discussion of the advantages that each technology brings to the CBRNE
detection effort.
A fully integrated UV Townsend Effect Plasma Spectroscopy (TEPS)-Raman Explosive Detection System (TREDS-2)
system has been constructed for use of standoff detection. A single 266nm Q-Switched Nd:YAG laser was used for
Raman excitation and TEPS plasma ignition. A nearly simultaneous 10.6μm CO2 laser was employed for the signal
enhancement in the TEPS measurements. TEPS and Raman spectra have been measured for a wide variety of energetic
samples on several different substrates. Chemometric techniques are presented for analysis and differentiation between
benign and energetic samples. Since these techniques are orthogonal, data fusion algorithms can be applied to enhance
the results. The results of the TEPS and Raman techniques along with their algorithms are discussed and presented.
The present work focuses on a new variant of double pulse laser induced breakdown spectroscopy (DP-LIBS) called
Townsend effect plasma spectroscopy (TEPS) for standoff applications. In the TEPS technique, the atomic and
molecular emission lines are enhanced by a factor on the order of 25 to 300 times over LIBS, depending upon the
emission lines observed. As a result, it is possible to extend the range of laser induced plasma techniques beyond LIBS
and DP-LIBS for the detection of CBRNE materials at distances of several meters.
In-situ trace detection of explosive compounds such as RDX, TNT, and ammonium nitrate, is an important
problem for the detection of IEDs and IED precursors. Spectroscopic techniques such as LIBS and Raman have
shown promise for the detection of residues of explosive compounds on surfaces from standoff distances. Individually,
both LIBS and Raman techniques suffer from various limitations, e.g., their robustness and reliability
suffers due to variations in peak strengths and locations. However, the orthogonal nature of the spectral and
compositional information provided by these techniques makes them suitable candidates for the use of sensor
fusion to improve the overall detection performance. In this paper, we utilize peak energies in a region by fitting
Lorentzian or Gaussian peaks around the location of interest. The ratios of peak energies are used for discrimination,
in order to normalize the effect of changes in overall signal strength. Two data fusion techniques are
discussed in this paper. Multi-spot fusion is performed on a set of independent samples from the same region
based on the maximum likelihood formulation. Furthermore, the results from LIBS and Raman sensors are
fused using linear discriminators. Improved detection performance with significantly reduced false alarm rates is
reported using fusion techniques on data collected for sponsor demonstration at Fort Leonard Wood.
A Deep-UV LIBS system has been constructed for the standoff detection of Explosives, and potentially Chemical,
Biological, Radiological, and Nuclear (CBRN) substances. A Q-Switched Nd:YAG Laser operating in at 266nm was
used for excitation of the LIBS plasma and future Raman excitation. This plasma was enhanced by the means of a nearly
simultaneous CO2 laser which results in a method referred to as Townsend Effect Plasma Spectroscopy (TEPS). Spectra
covering the range of 240-800nm at standoff distances are presented. The classical emission lines (i.e. C, N, O, H, etc)
of the energetic samples were observed and a peak ratio technique was used to differentiate between benign and
energetic samples of interest.
We have used a simultaneous 10.6 micron CO2 laser pulse to enhance the Laser Induced
Breakdown Spectroscopy (LIBS) emission from a 1.064 micron Nd:YAG laser induced plasma on a hard
target. The enhancement factor was found to be one or two orders of magnitude, depending upon the
emission lines observed and the target composition. The output energy of the 5 ns Nd:YAG laser pulse
was about 50 mJ and was focused to a 1 mm diameter spot to produce breakdown. The CO2 laser pulse
(100 ns spike, 5 microsec tail) had a similar energy density on target (0.06 J/mm2). Timing overlap of the
two laser pulses within 1 microsecond was important for enhancement to be observed.
Enhancement of neutral atomic emission was usually on the order of
5-20X, while enhancement of
ionized species tended to be higher, 10-200X. We attribute the increase in both the atmospheric
components and the +1 and +2 ionic emission to heating of the Nd:YAG plasma by the coincident CO2
laser. Such inverse bremsstrahlung absorption of CO2 laser radiation by the free electrons of plasma is well
known. We are conducting additional studies to better quantify the effects of laser beam mode, pulse-to-pulse
jitter, temporal pulse shaping, and optimization of these parameters for different LIBS target
compositions.
A pH sensor based upon spectrophotometric techniques has been developed for in-situ analysis of surface seawater. This sensor utilizes a spectrophotometric pH indicator (Thymol Blue) which has been calibrated for use in seawater as a function of temperature and salinity. Shipboard spectrophotometric pH analyses routinely demonstrate a precision on the order of plus or minus 0.0004 pH units. In- situ analysis of seawater pH has demonstrated a precision on the order of plus or minus 0.001 and an accuracy, using shipboard measurements as a standard, on the order of plus or minus 0.01. The sensor is a self-contained system which pumps seawater, meters in indicator, spectrophotometrically determines indicator absorbance and stores data with a 1 Hz acquisition frequency. The sensor employs two absorbance cells, each with three wavelength channels, to obtain the spectrophotometric absorbance. The sensor system, rated for depths up to 500 m, provides pH, conductivity, temperature and can be operated via computer or in a standalone mode with internal data storage. The sensor utilizes less than 12 watts of power and is packaged in a 29' long by 4.5' diameter aluminum housing.
KEYWORDS: Luminescence, Oxygen, Fiber optics sensors, Sensors, Digital signal processing, Signal attenuation, Fiber optics, Ruthenium, Optical fibers, Signal to noise ratio
An optical fiber fluorescence sensor system capable of compensating fiber bending loss is presented. The system utilized a modulated light-emitting diode and digital-signal processing chips to enhance the measurement of fluorescence signals. A fiber-optic oxygen sensor system suitable for measuring oxygen levels in gas and in aqueous media was developed, and the capability of the system to alleviate fiber bending loss was demonstrated. The signal-to-noise ratio of the system was found to exceed 30 dB using inexpensive components.
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