Adaptive estimation of Raman chemical mixture spectra

David J. Burr; Carl G. Chen; Arthur J. Sedlacek III

doi:10.1117/12.258153

12 November 1996 Adaptive estimation of Raman chemical mixture spectra

David J. Burr, Carl G. Chen, Arthur J. Sedlacek III

Proceedings Volume 2833, Application of Lidar to Current Atmospheric Topics; (1996) https://doi.org/10.1117/12.258153
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

We introduce an adaptive mixing algorithm for estimating the relative ratios of chemicals in a mixture spectrum. This procedure is particularly well suited to mixtures with a large dynamic range of mixture weights. It has the advantage of being able to be used in conjunction with a band-pass (difference-to-Gaussian or DOG) filter, and a correction of baseline off-set and tilting of the spectrum. Output of these filtering techniques is a cleaner signal retaining most of the relevant Raman spectral signature while minimizing artifacts due primarily to Rayleigh, dust, and atmospheric aerosols. We will describe the results of applying these algorithm to mixture spectra with both real and simulated additive noise.

Citation Download Citation

David J. Burr, Carl G. Chen, and Arthur J. Sedlacek III "Adaptive estimation of Raman chemical mixture spectra", Proc. SPIE 2833, Application of Lidar to Current Atmospheric Topics, (12 November 1996); https://doi.org/10.1117/12.258153

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