Progress in Standoff Surface Contaminant Detector Platform

Physical Sciences Inc. Progress in Standoff Surface Contaminant Detector Platform Julia R. Dupuis, Jay Giblin, John Dixon, Joel Hensley, David Mansur, and William J. Marinelli 20 New England Business Center, Andover, MA 01810 jdupuis@psicorp.com SPIE Defense and Security Micro- and Nanotechnology Sensors, Systems, and Applications IX April 13, 2017 20 New England Business Center Andover, MA 01810

Outline Technology overview Capability and program overview QCL surface contaminant detector platform concept Design Summary Transmitter/receiver QCL illuminator Speckle mitigation techniques Functional Test Results Conclusions -1

LWIR QCL based surface contaminant detector platform developed under IARPA s SILMARILS program Platform key attributes: Employs LWIR reflectance spectroscopy at standoff (10s of m) ranges Applicable to optically thick and thin materials including solid and liquid CWAs, TICs, TIMs, and explosives Applicable to gas detection via topographic back scatter LIDAR Speckle mitigated, detector noise limited performance enabling detection, discrimination regardless of surface coverage morphology and underlying substrate Capability Overview 5 or 30 m LWIR QCLs used to actively probe fundamental absorption features with highest spectral brightness available -3

Requirements for Key Performance Parameters -4 KPPs based on published program specifications Target and background library spans wide range of applications/missions Minimum detectable surface loading is ~ 10 to 100x lower than most standoff surface detection system requirements.

QCL Surface Contaminant Detector Concept Monostatic, integrated transmitter/receiver in a monolithic package including: A broadband QCL array transmitter proving continuous illumination over 900-1400 cm -1 used for flying spot illumination, An SHS snap shot receiver, A common transmitter/receiver foreoptic, A galvanometer mirror scanner located at a pupil plane to scan the coaligned illumination and receiver internal field of view (IFOV), Laser spectral power normalization, An SNR 1000 at all wavelengths using active speckle reduction, A reflective calibration target for illumination/collection spatial profile normalization, -5 A new variant of ACE featuring class-based screening. Spectral cube acquired by scanning QCL spot/shs IFOV

Offet Absorption Coefficient (/cm) Derived Key Performance Parameters -6 System Parameter Value Spectral range 950-1400 cm -1 Spectral resolution 8 cm -1 Noise equivalent reflectivity 0.1% FOR 1.9 IFOV 667 rad Response time 33 ms (5 m); 15 s (30 m) Spectral range based on targets NEr derived from discriminant spectral modulation imparted by optically thin film: 3.5E+04 3.0E+04 2.5E+04 CWA absorption coefficients (a SC ) A SC = α SC 2 t SC = 0. 001 where (Tabun) (Sarin) (Soman) (Cyclosarin) EA1699) 2.0E+04 1.5E+04 1.0E+04 5.0E+03 0.0E+00 900 1000 1100 1200 1300 Wavenumber (b) GA (Tabun) GB (Sarin) GD (Soman) GF (Cyclosarin) VX Vx (EA1699) HD L-3347 t SC = SC ρ SC = 10 7 cm for SC = 0. 1 μg/cm 2

Transmitter/Receiver Optical design enables achievement of all KPPs Minimum detectable surface coverage achieved via: Etendue set by external measurement geometry, Spatial diversity set by fore optics diameter and IFOV achieving sufficient speckle reduction Aerial coverage rate achieved via high speed scanning and interferogram acquisition. Transmitter/ Receiver Optical Layout Off-axis Radiometric Efficiency -8

QCL Illuminator Illuminator comprised of 5 Fabry-Perot, multimode QCLs in a common thermal assembly -9 QCLs are collimated and dichroically combined with OTS filters > 90% radiometric efficiency over 900-1400 spectral range Dichroic Configuration Each QCL driven with dedicated pulser board Pulse DC and drive current individually addressable to achieve optimal spectral shape All pulsers triggered with common, low frequency enable pulse train to synchronize on/off interferogram acquisition Photo of QCL Illuminator Solid model of QCL Illuminator Assembly

Performance Projections NESR vs. Range for Dt = 3 ms SNR with respect to discriminant signal: -10 where SNR = N surface A SC NESR N surface = SPD o ρ surface A spot π = unitless W = cm 2 ster cm 1 SNR vs. QCL SPD for r surface = 0.15 Etendue is limited by measurement geometry pixel binning only adds detector noise 10 mw/cm -1 SPD achieves SNR WRT discriminant signal > 10.

Custom QCL Development Five QCL designs are being developed by Alpes Lasers Based on proven LM InGaAs/AlInAs designs Key features: Double stacks to increase spectral width Range of device lengths and ridge widths to increase power and laser mode number Epi down mounting to increase power via colder junction temperature HR/AR coatings on back/front facets to increase power Electroluminescence spectra demonstrates good coverage of 900-1400 cm -1 spectral range Custom QCL Design Details Electroluminescence Spectra -11

Speckle Reduction NEr achieved through speckle reduction: Spatial diversity reduces speckle through averaging of speckle cells contained in IFOV Temporal diversity reduces speckle through time averaging of independent speckle patterns Additional diversity required: Wavelength and angular diversities are incompatible with CONOP Diversity balance provided by laser modes Total contrast: C total = C M/K C modes Predicted Contrast vs. QCL Spot Size at 30 m -12

Stock QCL Functional Testing: Objective: Baseline stock QCLs against KPPs for spectral range, SPD, and speckle Spectral range and SPD takeaways: Spectral Range and SPD Continuous broadband spectra achieved by tuning drive conditions 6 mm QCL produces > 10 mw/cm -1 (SPD KPP) at 20C 2x increase was measured from 3 to 6 mm cavity length validates power scaling Single stack achieves ~ 60 cm -1 spectral width custom double stack QCL projected to achieve > 120 cm -1-14 PSD vs. Optical Frequency at 20C Operating Temperature and 50% DC for 3 (left) and 6 mm (right)

Objective: Quantify speckle contrast using microbolometer camera for: Three spatial diversities: 6, 10, and 200 Two spectral widths: < 1 cm -1 and > 60 cm -1 High M achieved via spinning diffuser Key findings: Stock QCL Functional Testing: Speckle Reduction: Spatial Diversity Contrast scales with K -0.5 as expected Wavelength diversity does not impact speckle Pulsed operation results in significantly lower (better) contrast than predicted by C M/K -15 Measured Contrast vs. Spectral Width Spot cross sections for K = 6 (top) and 200 (bottom)

Stock QCL Functional Testing: Speckle Reduction: Temporal Diversity Objective: Determine requisite motion of diffuser to generate independent speckle patterns and sufficiently high M Speckle contrast measured as a function of diffuser relative motion Contrast calculated for cumulative frame averages Diffuser motion quantified directly from IR image Results show speckle decorrelates on the scale of surface (Infragold) correlation length, not receiver IFOV results support flying spot approach to achieve high M Frame Averaged QCL Spot Frame Averaged Speckle Contrast vs. Target Correlation Areas and vs. IFOVs -16

Conclusions A QCL-based standoff surface contaminant detector with application to solid, liquid, and gases for range of targets is being developed Sensor will resolve 0.1% reflectivity modulation enabling 0.1 g/cm 2 LOD at 30 m standoff LOD achieved through speckle reduction employing spatial, temporal, and laser mode diversities. Functional testing has demonstrated: Sufficiently spectrally bright QCLs are available, however, custom development will produce devices to cover 900-1400 cm -1 with no gaps. Requisite device spectral width and SPD appear achievable with double stack design based on performance of single stack stock QCLs. Laser mode diversity significantly reduces speckle noise below spatial and temporal diversity limit. Requisite temporal diversity is achieved by the flying spot approach. -18

Acknowledgements -19 This material is based upon work supported by United States Air Force under Contract Number FA8650-16-C-9109. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of United States Air Force. This research was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), through the AFRL contract FA8650-16-C-9109. All statements of fact, opinion or conclusions contained herein are those of the authors and should not be construed as representing the official views or policies of IARPA, the ODNI, or the U.S. Government. The Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.

-20 Questions? Julia R. Dupuis jdupuis@psicorp.com 978-738-8273