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Spectrally Resolved Laser-Induced Fluorescence Lidar Based Standoff Biodetection System

  • Jean-Robert SimardEmail author
  • Sylvie Buteau
  • Pierre Lahaie
Chapter
Part of the Integrated Analytical Systems book series (ANASYS)

Abstract

Over the years, rapidly monitoring wide areas for the presence of threatening bioaerosols has become an important objective for defense and public security. This chapter describes an important contending technology showing valuable capability to achieve that goal: Spectrally resolved laser-induced fluorescence lidars. After an introduction to this subject, the fundamental lidar theory associated with this specific technology is derived. Then, the robustness, specificity, and sensitivity of this technique to recognize the class of bioaerosols from a remote position are discussed. Subsequently, a statistical multivariate method based on the Mahalanobis distance to classify bioaerosols from their collected fluorescence induced spectral data is detailed. Finally, a conclusion reviews the key issues associated with this inelastic lidar technology as an important component of a complete threatening bioaerosol defense suite.

Keywords

Mahalanobis Distance Spectral Covariance Lidar System Aerosol Cloud Lidar Return 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Evans BTN, Roy G, and Ho J (1990) The detection and mapping of biological simulants V: statistical investigation of LCM limitation. Report DREV-4616/91 (Defence Research Establishment, Valcartier, Canada)Google Scholar
  2. 2.
    Tiee JJ, Hof DE, Karl RR, Martinez RJ, Quick CR, Cooper DI, Eichinger WE, Holtkamp DB (1992) Remote detection of biological particles and chemical plumes using UV fluorescence lidar. Paper presented at the 16th International Laser Radar Conference, Langley Research Center (NASA), USA, Part 1, p.189-192 (SEE N92-29228 20–35)Google Scholar
  3. 3.
    Simard J-R, Roy G, Mathieu P, Larochelle V, McFee J, Ho J (2004) Standoff sensing of bioaerosols using intensified range-gated spectral analysis of laser-induced fluorescence. In: IEEE Trans. on Geoscience and Remote Sensing 42(4): 865–874Google Scholar
  4. 4.
    Li J-K, Asali EC, Humphrey AE, Horvath JJ (1991) Monitoring cell concentration and activity by multiple excitation fluorometry. Biotechnology Progress 7(1): 21–27CrossRefGoogle Scholar
  5. 5.
    Chen RF (1990) Fluorescence of proteins and peptides. In: G. G. Guilbault (ed) Practical Fluorescence, 3rd ed. Marcel Dekker, New YorkGoogle Scholar
  6. 6.
    Gabor M (1999) Intrinsic Fluorescence of Proteins and Peptides. In: The Use of Fluorescence in Research into Protein Structures. Available on the Public Web. http://dwb.unl.edu/Teacher/NSF/C08/C08Links/pps99.cryst.bbk.ac.uk/projects/gmocz/fluor.htm). Accessed 7 Aug 2012
  7. 7.
    Dawson RB (1985) Data for biochemical research (3rd ed.). Clarendon Press, Oxford, 122Google Scholar
  8. 8.
    Lakowicz JR, Szmacinski H, Nowaczyk K, Johnson ML (1992) Fluorescence lifetime imaging of free and protein-bound NADH. Proc. Natl. Acad. Sci. U.S.A. 89 (4): 1271–1275CrossRefGoogle Scholar
  9. 9.
    Measures RM (1984) Laser-Remote-Sensor Equations. In: Laser Remote Sensing: Fundamentals and Applications. John Wiley & Sons, New YorkGoogle Scholar
  10. 10.
    Hill SC, Pinnick RG, Niles S, Pan YL, Holler S, Chang RK, Bottinger J, Chen BT, Orr CS, Feather G (1999) Real-time measurement of fluorescence spectra from single airborne biological particles. Field Analytical Chemistry and Technology, 3:221–239Google Scholar
  11. 11.
    Buteau S, Simard J-R, Rowsell S, Roy G (2010) Bioaerosol standoff detection and correlation assessment with concentration and viability point sensors. SPIE Europe Security and Defense: Optics and Photonics for Counterterrorism and Crime Fighting, SPIE 7838: 78380J1–78380J12Google Scholar
  12. 12.
    Manninen A, Putkiranta M, Saarela J, Rostedt A, Sorvajärvi T, Toivonen J, Marjamäki M, Keskinen J, Hernberg R (2009) Fluorescence cross sections of bioaerosols and suspended biological agents. Applied Optics, 48(22): 4320–4328CrossRefGoogle Scholar
  13. 13.
    Bronk BV, Reinisch L (1993) Variability of Steady-State Bacterial Fluorescence with Respect to Growth Conditions. Appl. Spectroscopy, 47:436–440CrossRefGoogle Scholar
  14. 14.
    Heaton H I (2005) Principal-components analysis of fluorescence cross-section spectra from pathogenic and stimulant bacteria. Applied Optics, 44(30):6486–6495CrossRefGoogle Scholar
  15. 15.
    Laflamme C, Simard J-R, Buteau S, Lahaie P, Nadeau P, Déry B, Houle O, Mathieu P, Roy G, Ho J, Duchaine C (2011) Effect of growth media and washing on the spectral signatures of aerosolized biological simulants. Applied optics, 50(6):788–796CrossRefGoogle Scholar
  16. 16.
    Hill SC, Mayo MW, Chang RK (2009) Fluorescence of Bacteria, Pollens, and Naturally Occurring Airborne Particles: Excitation/Emission Spectra. ARL-TR–4722Google Scholar
  17. 17.
    Agranovski V, Ristovski Z, Hargreaves M, Blackall PJ, Morawska L (2003) Performance evaluation of the UV APS: Influence of physiological age of airborne bacteria and bacterial stress. Journal of Aerosol Science, 34:1711–1727CrossRefGoogle Scholar
  18. 18.
    Christesen DS, Ong KK (1998) Fluorescence spectroscopy of biological agents - 1. Bacillusa Anthracis. Edgewood Research Development and Engineering Center report, ERDEC-TR–466Google Scholar
  19. 19.
    Steinvall O, Jonsson P, Kullander F (2007) Performance for a standoff biological warfare agent detection lidar. Proc. SPIE 6739: 673912.1-673912.14Google Scholar
  20. 20.
    Buteau S, Simard J-R, Déry B, Roy G, Lahaie P, Mathieu P, Ho J, McFee J (2006) Bioaerosols Laser-Induced Fluorescence provides specific robust signatures for standoff detection.Proc. SPIE 6378: 637813.1-637813.12Google Scholar
  21. 21.
    Buteau S, Stadnyk L, Rowsell S, Simard J-R, Ho J, Déry B (2007) Spectrally resolved Laser-Induced Fluorescence for bioaerosols standoff detection. Proc SPIE 6756: 08.1-08.10Google Scholar
  22. 22.
    Jensen GJ (2007) Effect of atmospheric background aerosols on biological agent detectors. Final technical report, Science Application International Corporation, VA, USAGoogle Scholar
  23. 23.
    Buteau S, Lahaie P, Rowsell S, Rustad G, Baxter K, Castle M, Foot V, Vanderbeek R, Warren R, Marquardt J, Baynard T (2008) Final Report for Task Group (RTG-55) on Laser based stand-off detection of biological agents. NATO RTO SET098 TG55 final reportGoogle Scholar
  24. 24.
    Farsund O, Rustad G, Kasen I, Haavardsholm TV (2010) Required spectral resolution for bioaerosol detection algorithms using standoff laser induced fluorescence measurements. IEEE Sensor Journal, 10(3):355–661CrossRefGoogle Scholar
  25. 25.
    Hopkins RJ, Barrington SJ, Castle MJ, Baxter KL, Felton NV, Jones J, Griffiths C, Foot V, Risbey K (2007) UV-LIF lidar for standoff BW aerosol detection. Proc. SPIE 7484:748409-748409-11Google Scholar
  26. 26.
    Buteau S, Ho J, Simard J-R, Lahaie P, McFee J, Roy G, Mathieu P, Déry B (2008) Bioaerosol standoff monitoring using intensified range-gated laser-induced fluorescence spectroscopy. In: Kim, Young J., Platt, Ulrich (Eds.) Advanced Environmental Monitoring, Chap. 16, Springer-Verlag, p. 203–216.Google Scholar
  27. 27.
    Cheng YS, Barr EB, Fan BJ, Hargis PJ, Rader DJ, O’Hern TJ, Torczynski JR, Tisone GC, Preppernau BL, Young SA and Radlioff RJ (1999) Detection of bioaerosol using multiwavelength UV fluorescence spectroscopy. Aerosol Science and Technology 30:186–201Google Scholar
  28. 28.
    Sivaprakasam V, Huston A, Scotto C, Eversole J (2004) Multiple UV wavelength excitation of bioaerosols. Opt. Express 12(19):4457Google Scholar
  29. 29.
    Huang HC, Pan YL, Hill SC, Pinnick RG, Chang RK (2008) Real-time measurement of dual-wavelength laser-induced fluorescence spectra of individual aerosol particles. Opt. Express 16(21):16523–16528Google Scholar
  30. 30.
    Pan YL, Hill SC, Pinnick RG, Huang H, Bottiger JR, Chang RK (2010) Fluorescence spectra of atmospheric aerosol particles measured using one or two excitation wavelengths: Comparison of classification schemes employing different emission and scattering results. Opt. Express 18:12436–12457Google Scholar
  31. 31.
    Mierczyk Z, Kopczyński K, Zygmunt M, Wojtanowski J, Młynczak J, Gawlikowski A, Młodzianko A, Piotrowski W, Gietka A, Knysak P, Drozd T, Muzal M, Kaszczuk M, Ostrowski R, Jakubaszek M (2011) Fluorescence/depolarization lidar for mid-range stand-off detection of biological agents. Proc. SPIE 8037:80371J.1–9Google Scholar
  32. 32.
    Carrano J, Jeys T, Cousins D, Eversole J, Gillespie J, Heally D, Licata N, Loerop W, O’Keefe M, Samuels A, Schultz J, Walter M, Wong N, Billote B, Munley M, Reich E, Roots J (2005) Chemical and Biological Sensor Standards Study. Defense Advanced Research Projects Agency, Department of Defense, DTIC, Fort Belvoir, VAGoogle Scholar
  33. 33.
    Buteau S, Simard J-R, Rowsell S (2009) Bioaerosol standoff detection simultaneously refereed with particle concentration (ppl) and viability units (ACPLA). Proc. SPIE 7484:748408.1–12Google Scholar
  34. 34.
    National Research Council of the national academies (2008) A framework for assessing the health hazard posed by bioaerosols. The National Academies Press, Washington, D.C.Google Scholar
  35. 35.
    Valdes JJ, Mohr J, Mackay R, Tunia E, Mara A (2010) Total Agent per Liter of Air With Particle Size Distribution (TALAp): A New Unit of Measure for the Test and Evaluation of Biodetectors. International Test and Evaluation Association Journal, 31:417–425Google Scholar
  36. 36.
    Buteau S, Simard J-R, Rowsell S, Roy G (2010) Bioaerosol standoff detection and correlation assessment with concentration and viability point sensors. Proc. SPIE 7838:78380J.1–12Google Scholar
  37. 37.
    Baker J (2011) US Army Dugway Proving Ground: DPG as the Chem/Bio MRTFB Activity. http://www.dtic.mil/ndia/2011test/11626WednesdayBaker.pdf, Accessed 20 Sep 2012
  38. 38.
    Ratnesar-Shumate S, Wagner ML, Kerechanin C, House G, Brinkley KM, Bare C, Baker NA, Quizon R, Quizon J, Proescher A, Van Gieson E, Santarpia JL (2011) Improved Method for the Evaluation of Real-Time Biological Aerosol Detection Technologies. Aerosol Science and Technology, 45:635–644Google Scholar
  39. 39.
    Theiler J, Wohlberg B (2012) Detection of spectrally sparse anomalies in hyperspectral imagery. Paper presented at IEEE Southwest symposium on Image Analysis and Interpretation (SSIAI), Santa Fe, NM, USA, Apr 2012Google Scholar
  40. 40.
    Poor HV (1994) An introduction to signal detection and estimation. 2nd edn. Springer-Verlag, New-YorkGoogle Scholar
  41. 41.
    Kelly EJ (1986) An adaptive detection algorithm. In: IEEE Transactions on aerospace and electronic systems, AES-22(2):115–127Google Scholar
  42. 42.
    Reed IS, Yu X (1990) Adaptive Multiple band CFAR detection of an optical pattern with unknown spectral distribution. In: IEEE Transactions on acoustics, Speech and Signal processing, 38(10): 1760–1770Google Scholar

Copyright information

© Springer-Verlag New York 2014

Authors and Affiliations

  • Jean-Robert Simard
    • 1
    Email author
  • Sylvie Buteau
    • 1
  • Pierre Lahaie
    • 1
  1. 1.Defence Research and Development Canada: Valcartier Research CentreQuebecCanada

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