Advanced mathematical frameworks for threat detection and identification

SpecInsight is an advanced spectral identification technology that utilizes a custom deep convolutional neural network to enhance the sensitivity and specificity of spectral analysis for target detection and identificaiton. Unlike traditional statistical approaches, SpecInsight considers both the characteristic sensor noise profile, as well as the similarities and differences in spectral signatures across the library. The SpecInsight technology uses vast amounts of nominal sensor measurements to characterize sensor variability, background environments, and common clutter. Target signatures are developed from only a few examples, and a custom sensor model is developed to inject representative sensor responses into the nominal background measurements.

SpecInsight has been successfully applied to Ion-mobility Spectrometers (IMS) and has demonstrated 10x increase in sensitivity and 100x reduction in false alarms over native and other state-of-the-art detection approaches. SpecInsight is the core detection and identification algorithm used in PSI’s Chemical Airborne Threat Sensor Suite (CATSS). CATSS is based on a water chemistry configuration of the Bruker RAID-P IMS interfaced with a processing module that executes SpecInsight to enable significantly improved performance against 12 chemical warfare agents (CWAs) and 20 toxic industrial chemicals and precursors. CATSS offers enhanced chemical vapor sensitivity, specificity, and false or clutter alarm rejection. The system is specifically configured to detect and localize a potential threat as early as the synthesis stage, and can be operated as a static node or can be integrated with a mobile platform. CATSS is offered as an add-on chemical detection module for PSI’s PERM-Mobile R/N mobile detection platform.

The core SpecInsight technology is sensor agnostic and PSI is currently working on applying its principles to detection modalities outside of IMS.