Digital Filtering Implementations for the Detection of Broad Spectral Features by Direct Analysis of Passive Fourier Transform Infrared Interferograms

Abstract

Finite impulse response (FIR) filters and finite impulse response matrix (FIRM) filters are evaluated for use in the detection of volatile organic compounds with wide spectral bands by direct analysis of interferogram data obtained from passive Fourier transform infrared (FT-IR) measurements. Short segments of filtered interferogram points are classified by support vector machines (SVMs) to implement the automated detection of heated plumes of the target analyte, ethanol. The interferograms employed in this study were acquired with a downward-looking passive FT-IR spectrometer mounted on a fixed-wing aircraft. Classifiers are trained with data collected on the ground and subsequently used for the airborne detection. The success of the automated detection depends on the effective removal of background contributions from the interferogram segments. Removing the background signature is complicated when the analyte spectral bands are broad because there is significant overlap between the interferogram representations of the analyte and background. Methods to implement the FIR and FIRM filters while excluding background contributions are explored in this work. When properly optimized, both filtering procedures provide satisfactory classification results for the airborne data. Missed detection rates of 8% or smaller for ethanol and false positive rates of at most 0.8% are realized. The optimization of filter design parameters, the starting interferogram point for filtering, and the length of the interferogram segments used in the pattern recognition is discussed.

Airborne passive Fourier transform infrared remote sensing of methanol vapor from industrial emissions

“…As has been described in a previous paper by Tarumi, in its interferogram representation, ethanol information is concentrated at a closer position to the centerburst than that of methanol. 19 Thus, with proper filter and segment selection, methanol and ethanol features can be well distinguished.…”

Quantitative determination of ethanol in heated plumes by passive Fourier transform infrared remote sensing measurements

“…This combination of windowing and bandpass filtering the interferogram has been used extensively in previous work. [14][15][16][17][18] In this research, a set of 13 time-dependent finite impulse response filters was developed for application to the interferogram data. 19 Filters 1-7 were designed to isolate the ethanol C-O stretching band at 1066 cm 21 .…”

Noise reduction in Raman spectra: Finite impulse response filtration versus Savitzky–Golay smoothing

“…from railway transport, 13 GSM mobile networks 14 and of course in physics 15 and chemistry. 21 In this work, we test the applicability of FIR filtration for noise removal from a full FT-Raman spectrum and also for correction of the background. 17 Some of the recently described applications of FIR filtration in molecular spectroscopy are limited to small parts of infrared interferograms, 18,19 a single vibrational band 20 or the identification of analytes with broad vibrational bands.…”