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Novel Image Segmentation Methods for Missile Attitude

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8649-20-P-0969
Agency Tracking Number: F19B-005-0159
Amount: $149,883.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF19B-T005
Solicitation Number: 19.B
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-03-06
Award End Date (Contract End Date): 2020-09-06
Small Business Information
1708 Jaggie Fox Way
Lexington, KY 40511
United States
DUNS: 014005016
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Manuel G Garcia Jr
 VP for Product Development
 (210) 863-3812
Business Contact
 Nalin Kumar
Phone: (817) 880-3880
Research Institution
 University of Texas at Arlington
 Jeremy Forsberg Jeremy Forsberg
701 S. Nedderman Dr
Arlington, TX 76019
United States

 (817) 272-2105
 Nonprofit College or University

Missile attitude in flight can be difficult to determine from ground-based images due to image resolution, lighting, object occlusion, and poor contrast. To address the need, UHV and UTARI propose a fusion based approach of 2 well proven methods to solve this problem. First, UHV Technologies will implement their existing innovative and state of the art machine learning methods for image segmentation of missiles during launch. These methods originated from an Advanced Research Project Association in the Department of Energy (ARPA-E) project to recycle metals, and was then improved by a United States Air Force (USAF) award to perform image segmentation based on UAV based aerial image data. Second, University of Texas at Arlington Research Institute (UTARI) will then take the segmented image data and then perform a feature-based pose estimation to determine the missile attitude using 3D alignment with a prior geometry database. The anticipated benefits include novel fusion-based approach deep learning algorithms to address this challenge, an image processing toolkit suitable for inclusion in current government owned analysis tools, and additionally commercial potential to address existing needs for low cost wide area ISR applications.

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

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