Raytheon Company

Erik D Johnson

Kalin Spariosu

Eric J Griffin

Bruce William Chignola

Brandon W Blackburn

Bernard Harris

Michael V Hynes

Anthony G Galaitsis

Richard A Moro, Jr

David W Payne

Liyi Dai

A method includes obtaining multiple data items from multiple heterogeneous data sources, where the multiple data items relate to an unmanned aerial system (UAS) flying in an area. The method also includes processing the multiple data items using a machine learning algorithm to determine a threat level of the UAS to one or more targets in the area. The method further includes outputting the threat level of the UAS for review by a user.

Threat assessment of unmanned aerial systems using machine learning

A detector apparatus is provided and includes a collector having access to a sample of a gaseous fluid and a tester coupled to and disposed remotely from the collector. The tester includes a test chamber into which a sample is directed from the collector, an excitation element to excite the sample in the test chamber and a spectrum analyzing device coupled to the test chamber to analyze the excited sample for evidence of a concentration of particles of interest in the gaseous fluid exceeding a threshold concentration. The threshold concentration is defined in accordance with a type of the particles of interest and a residence time of the sample.

Radioactive anomaly detector

Methods and apparatus for a detector system to detect gamma and neutron radiation. In one embodiment, a detector comprises a tank to hold a liquid, a plurality of tubes adjacent the tank to detect neutrons, and a plurality of photon detectors to detect Cherenkov light generated by gamma radiation in the liquid. The tank is configured to contain the liquid so that the liquid generates the Cherenkov light and moderates the neutrons.

Methods and apparatus for integrated neutron/gamma detector

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Boston, MA, United States of America

Erik D Johnson