IMPROVED IDENTIFICATION OF NOISY SPECTRA USING HIGHER ORDERED CORRELATION SPECTRAL-ANALYSIS

We used a higher-order correlation-based method of comparison for spec tral identification, sigher-order correlations are an extension of the more familiar second-order cross-correlation function and have the si gnificant advantage of being theoretically shown to eliminate noise of unknown spectral density under certain conditions, Specifically, we a pplied a third-order correlation technique to the identification of si milar IR spectra in the presence of noise. We were able to reduce the effects of noise from a second-order correlation measurement by furthe r processing the measurement with a third-order autocorrelation. Our r esults showed that the third-order correlation-based method increased the probability of detection of a spectrum in the presence of noise, w hen compared to using a second-order technique alone, The probability of detection increased enough at low signal-to-noise ratios that this technique may be useful when a second-order correlation technique is n ot acceptable, The third-order technique is applicable to a single exp eriment, but improved results were found by averaging the results of m ultiple experiments.