U.S. Department of Energy

Pacific Northwest National Laboratory

Compressive Sensing for Threat Detection

Principle Investigator: 

This project aims to develop signature discovery applications based on new "compressive sensing" algorithms, which reconstruct full resolution observations or signatures from data streams that are incomplete, corrupted, or under-sampled. The project addresses the problem of developing a signature-based detection capability that can handle rare event identification and improve sensor and signature robustness. In particular, the methodology has the ability to reconstruct features of interest in the presence of conditions that degrade signals or because of intentional obfuscation. This project is based on the new area of mathematics and algorithm research of compressive sensing, which augments data observations with additional information using iterative optimization techniques. This approach offers a powerful new signature analysis technique that has the potential to impact a wide range of applications.  

Project Staff: 
Andrew Stevens, Chandler May, Heather Orr, Yannan Sun, Curtis West
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PDF icon SDI_Compression_Sensing_flyer.pdf2.27 MB
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