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Utilizing ML Algorithms to Track and Identify UAS Threats

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: 6SVL4-22-P-0013
Agency Tracking Number: S222-002-0015
Amount: $149,853.25
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SOCOM222-002
Solicitation Number: 22.2
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-07-08
Award End Date (Contract End Date): 2023-01-30
Small Business Information
991 Discovery Drive
Huntsville, AL 35806-1111
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Keenan Kline
 (256) 971-1800
Business Contact
 Bob Sinclair
Phone: (256) 971-1800
Research Institution

The objective of this feasibility study is to assess the concept of using LiDAR to detect, track, and identify sUAS threats assisted by Artificial Intelligence (AI) agents. Inherent in this objective is concept development and feasibility assessment of Machine Learning (ML) and AI algorithms for creation and use of LiDAR target profiles for sUAS surveillance and identification. This objective will be satisfied with fact-based recommendations for an overall system design to improve sUAS detection, provide real-time alerts and geolocate sUAS in flight. During this phase, the team will investigate the availability and suitability of LiDAR sensors to address the following issues: a) Detection and tracking of sUAS in flight; b) Discrimination and identification of sUAS; c) Capability to integrate with other C-UAS sensors; d) Integration of AI/ML fusion applications; and e) Contribution to a 3D object mapping library. We will assess the performance of LiDAR sensors using the following criteria: a) Detection – range, accuracy, and completeness; b) Geospatial accuracy; c) Track accuracy and completeness; d) Capability of producing target profiles supporting rapid identification and object discrimination; and e) Considerations of Size, Weight, and Power (SWaP) and durability of the LiDAR system.

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

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