Echo Ridge, LLC — Department of Defense STTR Phase I: ABSTRACT: Echo Ridge proposes to develop a suite of EW training tools to support realisti

Echo Ridge, LLC — STTR Phase I award from Department of Defense.

Amount
$149,991
Agency
Department of Defense · Air Force
Program / Phase
STTR · Phase I
Solicitation
2014.A
NAICS
Place of performance
VA
Period
2014-09-29 → 2015-06-29

Description

ABSTRACT: Echo Ridge proposes to develop a suite of EW training tools to support realistic warfighter training in the congested and contested RF environments expected in future operational engagements. The tools consist of an opposing force broadcast capability, an EMS monitoring capability and an analytical framework for configuring and scoring the behavior of the tools and participating warfighters. The broadcast device is based on our existing fielded Wideband Instrumented Streaming Platform (WISP) product. The EMS monitoring device is based on our in-development 2nd generation Handheld Signal Processor (HASP). Our SAIJ software application (Software Architecture for Intelligent Jamming) will run on the HASP platform, and provide the EMS monitoring capability enabling automated spectrum monitoring, analysis and characterization. We will use the SAIJ open architecture features to incorporate cyclostationary signal processing (CSP) spectrum detection and analysis signal processing software. Given the extensive re-use of previously Government sponsored R & D, we propose to perform risk reduction testing as part of Phase I for key functions for broadcast and EMS monitoring nodes in a realistic laboratory environment using Echo Ridge's DYnamic Spectrum Environment emulator (DYSE) test asset. BENEFIT: The results of the proposed research will benefit the EW training community by providing cost effective and realistic EW training tools. It will allow EW-related training exercises to include emulated opposing force broadcasts, and warfighters to train using tools that address modern electronic communications technologies. It will also create a new analytic framework for quantitatively evaluating EW scenarios. This framework will be useful to the training community as well as the broader EW community. Given the open architecture and COTS basis for the developed nodes, they will be useful in transitioning new EW technologies from the laboratory to the field.