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31 October 1997 Algorithms for the extraction of chemical absorption signatures in lidar time series
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Chemical absorption signatures in lidar data can be difficult to identify when the signal to noise ratio is small. For lidar interrogation of unknown chemical mixtures it is advantageous to sample with many different wavelengths, covering the largest possible absorption bandwidth. A more effective DIAL measurement can be made if one known a priori which wavelengths will be absorbed by the unknown chemical(s). An algorithm has been developed which quickly identifies the absorbed laser lines by examining the temporal cross-correlation between wavelengths. Once this determination has been made the remote chemical mixture can be re-sampled with fewer wavelengths resulting in higher data rats at the sensitive wavelengths. This algorithm was shown to be successful with actual DIAL measurements of remote chemical mixtures. A second detection algorithm will also be presented that uses the temporal autocorrelation at a single wavelength to detect the presence of a time dependent chemical absorption, e.g. form a chemical plume, in a noisy time series. The overall DIAL sensitivity using these algorithms will be compared with standard methods.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Edward P. MacKerrow, Brian D. McVey, Mark J. Schmitt, and Joseph J. Tiee "Algorithms for the extraction of chemical absorption signatures in lidar time series", Proc. SPIE 3127, Application of Lidar to Current Atmospheric Topics II, (31 October 1997);


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