Signal Intelligence (SIGINT) Sensing Modules
Past New Requirement Updated
- Agency
-
Navy NAVAIR Naval Air Warfare Center Weapons Division
Naval Air Warfare Center, Department of Defense
- Solicitation expected
- Estimated value
- $7,500,000 to $50,000,000
- Set-aside
- No set-aside
Forecast facts
- Anticipated award
- Through
- NAICS code
- 541715 Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- Place of performance
- Point Mugu, CA
- Forecast number
- N68936-25-RFPREQ-450000E-0004
Forecast details come from the Navy's Long Range Acquisition Estimates. Agencies' dates and values are estimates.
About this forecast
The Department of the Navy Naval Air Systems Command Naval Air Warfare Center Weapons Division is conducting a sole-source Phase III Small Business Innovative Research (SBIR) effort under AF222-D025 for development of advanced signal-processing modules that prepare the signal environment to identify and mitigate interfering signals and support detection, identification, and collection of target Signals of Interest, incorporating machine learning algorithms to adapt to changing signal environments while maintaining mission capabilities. The solicitation is estimated to release on April 1, 2026, with award anticipated on July 1, 2026.
The estimated award value ranges from $7.5 million to $50 million under a single-award indefinite-delivery contract with cost-reimbursement pricing and a 36-month period of performance. Work is performed at Point Mugu, California. Personnel and facilities clearances at the Secret level are required. The contracting office is NAWCWD (UIC N68936), with the program requirement office identified as D52/E52 NAWCWD.
Forecast text
Phase III Small Business Innovative Research (SBIR) effort under AF222-D025 for development of an advanced signal-processing modules that assist with preparation of the signal environment to identify and mitigate interfering signals and to support detection, identification, and collection of target Signals of Interest (SOI) as well as utilizing machine learning algorithms to adapt to changing signal environments while maintaining mission capabilities.
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