Optimization of a chemical identification algorithm

Thomas H. Chyba; Brian Fisk; Christin Gunning; Kevin Farley; Amber Polizzi; David Baughman; Steven Simpson; Mohamed-Adel Slamani; Robert Almassy; Ryan Da Re; Eunice Li; Steve MacDonald; Ahmed Slamani; Scott A. Mitchell; Jay Pendell-Jones; Timothy L. Reed; Darren Emge

doi:10.1117/12.850529

15 April 2010 Optimization of a chemical identification algorithm

Thomas H. Chyba, Brian Fisk, Christin Gunning, Kevin Farley, Amber Polizzi, David Baughman, Steven Simpson, Mohamed-Adel Slamani, Robert Almassy, Ryan Da Re, Eunice Li, Steve MacDonald, Ahmed Slamani, Scott A. Mitchell, Jay Pendell-Jones, Timothy L. Reed, Darren Emge

Author Affiliations +

Proceedings Volume 7698, Signal and Data Processing of Small Targets 2010; 76980A (2010) https://doi.org/10.1117/12.850529
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

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Thomas H. Chyba, Brian Fisk, Christin Gunning, Kevin Farley, Amber Polizzi, David Baughman, Steven Simpson, Mohamed-Adel Slamani, Robert Almassy, Ryan Da Re, Eunice Li, Steve MacDonald, Ahmed Slamani, Scott A. Mitchell, Jay Pendell-Jones, Timothy L. Reed, and Darren Emge "Optimization of a chemical identification algorithm", Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 76980A (15 April 2010); https://doi.org/10.1117/12.850529

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