SBIR/STTR Research Award

Noise Parameter Characterization of G-Band Amplifiers

Award identifier 1f3325e0e872c054998cbd2d2a74271a6021e172b9df0aaea3d38dcce03486beAwarding agency Department of Defense · Defense Advanced Research Projects Agency

Award amount

$1,799,953

Program and phase

SBIR · Phase II – Direct to Phase II

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Defense Advanced Research Projects Agency
Recipient company
VIRGINIA DIODES, INC.
Proposal award date
2022-12-06
Contract end date
2024-12-11
UEI
VJ9NDNJEG6G4
Solicitation number
22.4
Topic code
HR0011SB20224-12

Research abstract

The goal of this project is to develop the technology needed for on-wafer characterization of new MMICs and amplifiers across the 110 ¢ 300 GHz frequency range. ĀThis goal requires successful completion of the proposed Phase II effort as well as follow-on research and development to develop commercial systems and further extend the frequency range. The specific goals of this Direct to Phase II (DP2) proposal are i) the development of the high VSWR mechanical tuners which are critical for noise and load-pull measurements in this frequency range, and ii) the demonstration of an on-wafer noise characterization system at 220 GHz to be delivered to a government laboratory for initial evaluation and to support of the DARPA ELGAR program. The proposers for this effort are Maury Microwave Corporation (Maury) and Virginia Diodes, Inc. (VDI), with each conducting roughly half of the R&D. The focus of MauryÆs Phase II effort is the development and demonstration of the higher frequency mechanical tuners and the implementation of the prototype 220 GHz system. Maury is an established leader in microwave measurement systems, with particular expertise in the development of advanced microwave tuners. Through their previous work, Maury has demonstrated the 110 GHz tuner performance required for DP2 consideration, as described in the solicitation topic. The feasibility of extending this previous work to at least 300 GHz is presented in this proposal. VDIÆs Phase II work will emphasize the advancement of other critical subsystems for noise characterization, specifically the VNA frequency extenders, noise sources and frequency down-converters. One of the primary challenges of extending measurement capabilities to higher frequencies is the increased losses of passive elements such as the mechanical tuners and on-wafer probes. Through the improvement of each of the subsystems, VDI will alleviate the impact of the increased losses. Specifically, VDI will increase the power available from the VNA extenders and noise sources, while also improving the sensitivity of the down-conversion receivers. This effort is critical to ensure that the resulting measurement systems have sufficient performance to meet DARPAÆs needs as well as to achieve commercial success.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

46 SBIR/STTR records share this UEI (2001–2025). Reported award amounts total $19,040,176. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: National Aeronautics and Space Administration, Department of Defense, Department of Energy, Department of Health and Human Services, Department of Homeland Security, Department of Commerce

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.