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PLUMESIGHT: LIDAR-Based Plume Classification

Award Information
Agency: Department of Defense
Branch: Office for Chemical and Biological Defense
Contract: W911SR-22-C-0010
Agency Tracking Number: C2-0603
Amount: $549,883.48
Phase: Phase II
Program: SBIR
Solicitation Topic Code: CBD202-002
Solicitation Number: 20.2
Solicitation Year: 2020
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-02-14
Award End Date (Contract End Date): 2024-02-13
Small Business Information
1777 Highland Drive Suite B
Ann Arbor, MI 48108-2285
United States
DUNS: 969868298
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Matthew Lewis
 (734) 276-8359
Business Contact
 Erick Finkiewicz
Phone: (734) 975-8777
Research Institution

In battlefield environments, the atmosphere is littered with aerosols from a variety of sources: dust from vehicles and foot traffic; smoke from firearms and explosives; and, potentially, plumes of weaponized aerosols. In order to improve situational awareness, it is critical to develop a real-time knowledge of the presence, type, and structure of aerosol plumes on the battlefield. Elastic LIDAR systems are powerful remote sensing tools capable of detecting, quantifying, and classifying clouds of aerosols.LIDAR instruments have a long history of use in atmospheric remote sensing for making measurements of atmospheric aerosol types and concentrations. Beyond atmospheric science, LIDAR has use in the measurement and quantification of man-made aerosol releases ranging from smoke grenades to chemical explosives to anthrax.To extend the ability of LIDAR systems tocharacterize and classify plumes in cluttered environments, Michigan Aerospace Corporation proposes to further develop itsplumesight algorithm. Operating on raw LIDAR backscatter returns, the plumesightalgorithmreconstructs high fidelity images of the plumeusing machine learning algorithms, and then usesdeep convolutional recurrent networksto learn how plumes of differentsubstances evolve over time. By exploiting these complex spatiotemporal patterns, the plumesight algorithm is able to classify plumes using elastic LIDAR returns.

* Information listed above is at the time of submission. *

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