An active spectrophotopolarimeter sensor and support system were developed for a military/civilian defense feasibility study concerning the identification and standoff detection of biological aerosols. Plumes of warfare agent surrogates gamma-irradiated Bacillus subtilis and chicken egg white albumen (analytes), Arizona road dust (terrestrial interferent), water mist (atmospheric interferent), and talcum powders (experiment controls) were dispersed inside windowless chambers and interrogated by multiple CO(2) laser beams spanning 9.1-12.0 microm wavelengths (lambda). Molecular vibration and vibration-rotation activities by the subject analyte are fundamentally strong within this "fingerprint" middle infrared spectral region. Distinct polarization-modulations of incident irradiance and backscatter radiance of tuned beams generate the Mueller matrix (M) of subject aerosol. Strings of all 15 normalized elements {M(ij)(lambda)/M(11)(lambda)}, which completely describe physical and geometric attributes of the aerosol particles, are input fields for training hybrid Kohonen self-organizing map feed-forward artificial neural networks (ANNs). The properly trained and validated ANN model performs pattern recognition and type-classification tasks via internal mappings. A typical ANN that mathematically clusters analyte, interferent, and control aerosols with nil overlap of species is illustrated, including sensitivity analysis of performance.
The complete 16-element Mueller matrices for backscattering from amino acids, sugars, and other enantiomorphic compounds pressed into wafer form were measured at infrared wavelengths. For each compound a pair of CO(2) laser lines was selected from the 9.1-11.6-mum region such that one line excited an absorption band in the compound, whereas the other did not. It was observed that at least some of the matrix elements differed significantly depending on which of the two wavelengths was used in the measurement. We propose that a neural network pattern recognition system can be trained to detect the presence of specific compounds based on multiwavelength backscatter Mueller matrix measurements.
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