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Selection of an averaging technique by simulation study of a DIAL system for toxic agents monitoring
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Paper Abstract

Differential Absorption Lidar (DIAL) is a very effective technique for standoff detection of various toxic agents in the atmosphere. The Lidar backscattered signal received usually has poor signal to noise (SNR) ratio. In order to improve the SNR, statistical averaging over a number of laser pulses is employed. The aim of the present work is to select a particular statistical averaging technique, which is most suitable in removing the noise in Lidar return signals. The DIAL system considered here uses laser transmitters based on OPO based (2-5 μm) and TEA CO2 (9-11μm) lasers. Eight commonly used chemical warfare agents including five nerve agents and three blister agents have been considered here as examples of toxic agents. A Graphical User Interface (GUI) software has been developed in LabVIEW to simulate return signals mixed with the expected noise levels. A toxic agent cloud with a given thickness and concentration has been assumed to be detected in the ambient atmospheric conditions at various ranges up to 5 Km. Data for 200 pulses per agent was stored in the computer memory. Various known statistical averaging techniques were used and number concentrations of particular agent have been computed and compared with ideal Lidar return signal values. This exercise was repeated for all the eight agents and based on the results obtained; the most suitable averaging technique has been selected.

Paper Details

Date Published: 3 October 2007
PDF: 9 pages
Proc. SPIE 6750, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing III, 67501E (3 October 2007); doi: 10.1117/12.737022
Show Author Affiliations
Jai Paul Dudeja, Laser Science and Technology Ctr. (India)
Mukesh Kumar Jindal, Laser Science and Technology Ctr. (India)
S. Veerabuthiran, Laser Science and Technology Ctr. (India)

Published in SPIE Proceedings Vol. 6750:
Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing III
Upendra N. Singh; Gelsomina Pappalardo, Editor(s)

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