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We describe a principal component analysis (PCA) of bio-aerosols which incorporates both fluorescence excitation-emission data over the excitation range 210 nm - 600 nm and lifetime data. The analysis suggests a useful separation metric based on spectral angle.
We describe a new method for background suppression and agent detection in principal component spaces derived from spectroscopic data to develop an improved trigger sensor for bioaerosol detection. Simulation results and laboratory data are shown.
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