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Expedition Technology, Inc. SBIR Phase I Award, August 2019

Improved detection sensitivity, geolocation accuracy, and create novel GEOINT products for OTHR radar systems (IGOR).

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sbir.gov/node/1845247
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Expedition Technology Inc
Expedition Technology Inc
0
Government Agency
U.S. Department of Defense
U.S. Department of Defense
0
Government Branch
National Geospatial-Intelligence Agency
National Geospatial-Intelligence Agency
0
Award Type
SBIR0
Contract Number (US Government)
HM047619C00760
Award Phase
Phase I0
Award Amount (USD)
99,9840
Date Awarded
August 13, 2019
0
End Date
May 18, 2020
0
Abstract

Over the Horizon Radar (OTHR) has been a deployed capability for over 3 decades. OTHR uses the ionosphere to reflect HF radar signals in order to illuminate objects (potential targets) beyond the horizon, giving it a potential effective range of several hundred to a few thousand kilometers. Understanding how the HF radar signals interact and reflect off the ionosphere is crucial to accurate target detection and geolocation, and current state-of-the-art techniques only provide a range accuracy of about ten to forty kilometers. Expedition Technology, Inc. (EXP) and Applied Ocean Science, Inc. (AOS) are pleased to provide Improved Geolocation for OTH Radar (IGOR), which incorporates an innovative. Machine Learning based generative model of the propagation channel in order to refine geolocation estimates and increase the accuracy of range and Doppler measurements. It is also expected that the generative propagation modeling will provide additional utility outside of the OTHR system. Leveraging EXP’s experience in ionospheric modeling, advanced signal processing, and machine learning, At a high level, the problem reduces to a nonlinear, multidimensional estimation problem, with noisy and imperfect data. Since they fundamentally operate in a nonlinear N-dimensional space, Machine Learning (ML) approaches often significantly outperform alternative or traditional approaches.

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