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CT-ID: Contextual Threat Identification

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0860-22-C-7063
Agency Tracking Number: B212-019-0049
Amount: $149,998.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: MDA21-019
Solicitation Number: 21.2
Timeline
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2021-12-06
Award End Date (Contract End Date): 2022-06-05
Small Business Information
1221 Brickell Ave., Suite 900
Miami, FL 33131-0000
United States
DUNS: 079640621
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Stanislav Shalunov
 (415) 601-7021
 stas@clostra.com
Business Contact
 Gregory Thiele
Phone: (415) 377-8051
Email: gthiele@clostra.com
Research Institution
N/A
Abstract

Traditional deep learning (DL) classifiers often ignore contextual data, limiting complex threat scenario analysis. A new approach, incorporating a wide range of contextual data, is needed to improve object of interest classification, tracking, and targeting. Clostra’s CT-ID (Contextual Threat Identification) will incorporate multi-sensor, time-series, and high-level contextual data, improving threat classification accuracy and allowing salvo firing control to confidently target high-priority objects. Approved for Public Release | 21-MDA-11013 (19 Nov 21)

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

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