Wavelet-Based Approach for Signal Processing and Analysis

To respond to the U.S. military requirement for new tools to provide early warning on the existence of chemical/biological contamination in the battlefield, Physical Optics Corporation (POC) proposes to further develop Plume Analysis and Classification for Early Warning (PEACE). PEACE is designed to process LIDAR detection of plume clouds and extract key information by determining the plume’s content and estimating the method used to release chemical/biological contaminants in the environment. PEACE uses machine learning (ML) and artificial intelligence (AI) algorithms to detect contaminant material type and release method. ML/AI algorithms classify the plumes into a set of known contaminants and compute the confidence levels for the classification results. PEACE improves the classification accuracy by selecting ML/AI algorithm parameters (such as number of distinguishable classes of contaminants) that are sensitive to ambient conditions and fine-tuned to contaminant(s) of interest. Under this Sequential Phase II project, the PEACE algorithms successfully developed during Phase II project WASP will be matured further by refining the ML/AI algorithms, incorporating a standard modular Common CBRN Sensor Interface (CCSI)-compliant framework, and demonstrating performance improvements by using an extensive set of data. PEACE is designed for eventual integration with a Stryker sensor suite.