Electrical & Computer Engineering, Department of


First Advisor

Dennis R. Alexander

Date of this Version


Document Type



Thomas, William C. Ultrashort Cross-Correlation in the Middle Infrared: A Novel Approach to Standoff Detection. 2019. University of Nebraska-Lincoln, PhD dissertation.


A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Doctor of Philosophy, Major: Electrical Engineering, Under the Supervision of Dennis R. Alexander. Lincoln, Nebraska: April, 2019.

Copyright (c) 2019 William "Conner" Thomas


Lasers are a common tool in standoff detection because of their small divergence, large amount of power, and multiple wavelengths available for optical interaction. Optical signatures of targets can be composed of but are not limited to absorption, fluorescence, backscatter, polarization manipulation, and plasma spectra. This work was an investigation of a new signature phenomenon: Dispersion of middle infrared ultrashort laser pulses through gas and vapor phase molecules. Vibrational and rovibrational absorption lines of molecular species affect the spectral phase and spectral amplitude of ultrashort light pulses leading an inititally gaussian temporal profile to become distorted. This dissertation is an exploration of these temporal signatures for various concentrations of H2O, CO2, CH4, CF4, and dimethyl methylphosphonate which is a common simulant for the nerve agent, Sarin. By tuning the wavelength to a rovibrational resonance, unique temporal signatures were observed for each molecule. Experimental results were corroborated by simulations based on gas spectra and the Kramers-Kronig transformation. This is one of the few times that this phenomenon has been reported for non-atmospheric molecules.

A novel improvement in the signal-to-noise ratio of the ultrashort pulse signatures was developed by measuring the cross-correlated four-wave-mixing output with an amplified photodiode and lock-in amplifier. Principal component analysis was used to successfully discriminate the optical signatures. The signatures did not have a linear relationship with respect to molecular concentration as in other laser-based standoff techniques. Therefore, the MATLAB regression learner toolbox was used to trend the data for quantitative prediction. Sensitivity of the proposed technique was analyzed in comparison to the state-of-the-art.

Adviser: Dennis R. Alexander