Estimating the backscatter spectral dependence and relative concentration for multiple aerosol materials from lidar data

Russell E. Warren; Richard G. Vanderbeek

doi:10.1117/12.541548

13 August 2004 Estimating the backscatter spectral dependence and relative concentration for multiple aerosol materials from lidar data

Russell E. Warren, Richard G. Vanderbeek

Author Affiliations +

Proceedings Volume 5416, Chemical and Biological Sensing V; (2004) https://doi.org/10.1117/12.541548
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

Detection and estimation of materials in the atmosphere by lidar has heretofore required that the spectral dependence of the relevant cross section coefficients -- backscatter in the case of aerosols and absorptivity for vapors -- be known in advance. While this typically is a reasonable assumption in the case of vapor, the aerosol backscatter coefficients are complicated functions of particle size, shape, and refractive index, and are therefore usually not well characterized a priori. Using incorrect parameters will give biased concentration estimates and impair discrimination ability. This paper describes an approach for estimating both the spectral dependence of the aerosol backscatter and relative concentration range-dependence of a set of materials using multi-wavelength lidar. The approach is based on state-space filtering that applies a Kalman filter in range for concentration, and updates the backscatter spectral estimates through a sequential least-squares algorithm at each time step. The method is illustrated on aerosol-release data of the bio-simulant ovalbumin collected by ECBC during field tests in 2002, as well as synthetic data sets.

Citation Download Citation

Russell E. Warren and Richard G. Vanderbeek "Estimating the backscatter spectral dependence and relative concentration for multiple aerosol materials from lidar data", Proc. SPIE 5416, Chemical and Biological Sensing V, (13 August 2004); https://doi.org/10.1117/12.541548

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available