FA864924P0176
Purchase Order
Overview
Government Description
Gargoyle: generative artificial intelligence radio frequency geospatial overlays for localization of emitters
Awardee
Awarding / Funding Agency
Place of Performance
Herndon, VA 20171 United States
Pricing
Fixed Price
Set Aside
Small Business Set Aside - Total (SBA)
Extent Competed
Full And Open Competition After Exclusion Of Sources
Related Opportunity
None
Knowmadics was awarded
Purchase Order FA864924P0176 (FA8649-24-P-0176)
for Gargoyle: Generative Artificial Intelligence Radio Frequency Geospatial Overlays For Localization Of Emitters
worth up to $74,585
by Air Force Research Laboratory
in December 2023.
The contract
was awarded
with a Small Business Total set aside
with
NAICS 541715 and
PSC AC32
via direct negotiation acquisition procedures with 999 bids received.
SBIR Details
Research Type
Small Business Innovation Research Program (SBIR) Phase I
Title
GARGOYLE: Generative AI RF Geospatial Overlays for Localization of Emitters
Abstract
In urban areas, localizing Radio Frequency (RF) emitting sources is complicated by multipath propagation, where signals bounce off structures and create multiple paths between emitter and receiver. This interferes with localization algorithms and TTPs that assume a single, direct signal path. GARGOYLE uses applied AI to characterize available GIS data, it then leverages this understanding along with near-real-time on-target signal sensors to apply a combination of methods (e.g., ray tracing, particle-based simulation) to simulate and predict RF propagation for candidate emitters as a mechanism to facilitate improved electronic warfare (EW) mission planning and execution. GARGOYLE intends to present this information through both 2D tablet and 3D Augmented Reality (AR) sandtable visualizations (validated at a recent AFSOC-supported T&E event) to provide Operators with actionable intel. GARGOYLE seeks to provide SOF EW Operators with a tool for near-real time 3D RF signal propagation modeling that uses generative AI to contextualize models to dense urban environments (via GIS data) to facilitate more rapid and accurate localization of RF emitting devices (e.g., a target s smartphone) during direction finding (DF ing) or similar threat detection & characterization TTPs. This will both enhance Operator survivability (by enabling them to spend less time in potentially hostile regions and have more refined plans for where they need to run survey and DF ing TTPs) and increase Operator situational awareness (SA; through better understanding of RF terrain) ultimately improving the likelihood of positive mission outcomes.
Research Objective
The goal of phase I is to establish the technical merit, feasibility, and commercial potential of proposed R&D efforts and determine the quality of performance of the small business awardee organization.
Topic Code
AFX237-PCSO1
Agency Tracking Number
FX237-PCSO1-0029
Solicitation Number
X23.7
Contact
Meghan Scott
Status
(Complete)
Last Modified 12/13/23
Period of Performance
12/13/23
Start Date
3/13/24
Current End Date
3/13/24
Potential End Date
Obligations
$74.6K
Total Obligated
$74.6K
Current Award
$74.6K
Potential Award
Award Hierarchy
Purchase Order
FA864924P0176
Subcontracts
Activity Timeline
People
Suggested agency contacts for FA864924P0176
Competition
Number of Bidders
Not Applicable For Award Type
Solicitation Procedures
Negotiated Proposal/Quote
Evaluated Preference
None
Performance Based Acquisition
Yes
Commercial Item Acquisition
Commercial Item
Simplified Procedures for Commercial Items
No
Other Categorizations
Subcontracting Plan
Plan Not Required
Cost Accounting Standards
Exempt
Business Size Determination
Small Business
Defense Program
None
DoD Claimant Code
None
IT Commercial Item Category
Not Applicable
Awardee UEI
KB84PWSQTDK4
Awardee CAGE
6ZUE3
Agency Detail
Awarding Office
FA8649 FA8649 USAF SBIR STTR CONTRACTING
Funding Office
F4FBEQ
Created By
renee.west@us.af.mil
Last Modified By
stephanie.rosenthal.fa4497
Approved By
stephanie.rosenthal.fa4497
Legislative
Legislative Mandates
None Applicable
Performance District
VA-11
Senators
Mark Warner
Timothy Kaine
Timothy Kaine
Representative
Gerald Connolly
Modified: 12/13/23