What project 642597 buys
Non-cooperative combat identification (CID) employs multiple sensing technologies and signal processing techniques designed to extract discriminating features from a battlespace entity (target). Specifically designed algorithms compare those extracted features to a tailored database to identify those targets. This is the primary method for advanced CID development and the key enabler for aiding Air Force kill-chains in denied access environments. These technologies include: (A) non-cooperative Air Target Identification (ATID) technologies, (B) non-cooperative Ground Target Identification (GTID) technologies, and (C) Studies evaluating potential new technologies. ATID development focuses on platform-centric CID technologies that enhance capability to determine enemy air threats. A primary area of focus is the development/implementation of the government-owned joint standard for CID, Joint Multi-platform Advanced Combat identification (JMAC) architecture shared/implemented by Army, Air Force, Navy, and MDA; it fuses multiple sensors to provide a robust, advanced CID solution aimed at the discovery/generation of CID features from fielded sensors. JMAC is one of three key technologies in the Missile Defense Agency's Joint Tactical Integrated Fire Control (JTIFC) Architecture, as such it is being adopted for homeland defense. Other areas of focus include combat identification technologies that broaden the application of CID across air platforms utilizing larger air-to-air kill-webs planned for employment by the Air Force and utilize assets in unmanned aerial systems and space to improve and enable CID in future threat air engagements. GTID development focuses on platform-centric CID technologies that enhance capability to determine priority enemy ground threat systems (both offensive and defensive systems). Primary areas of focus include transitioning CID capability for denied access environments using passive radio frequency and electronic warfare information, integrating radio-based technologies into the cockpit to increase confidence of target identification and situational awareness as well as reduce fratricides, and to demonstrate weapon-based combat identification back to the launch platform using a communication link from that launched weapon.
- Product Development
- Management Services
Project 642597 funding, FY2025–FY2031
Prior years are actuals, the budget year is the request, and the outyears are the FYDP plan. Estimate types are colored and never summed into one figure. Projects carry the full five-year plan; the activities inside them stop at the budget year.
| Fiscal Year | Estimate Type | Amount ($M) |
|---|---|---|
| FY2025 | Actual | 14.9 |
| FY2026 | Enacted | 22.0 |
| FY2027 | Request | 22.9 |
| FY2028 | Outyear | 22.9 |
| FY2029 | Outyear | 23.3 |
| FY2030 | Outyear | 23.8 |
| FY2031 | Outyear | 24.3 |
3 accomplishments / planned programs
The R-2A exhibit — the only level of the budget that describes work that has not happened yet. Activities carry the prior, current and budget year only, no five-year plan. 1 of them describes FY2027 work in enough detail to have its own page; the rest are shown here in full. Coverage is partial across the corpus, so count activities, never total them.
-Continue maturation of air target sensor feature extraction algorithms for implementation with the JMAC CID framework. -Complete maturation and effectiveness testing of the JMAC air target algorithms on F-15. -Continue expansion of sensor feature extraction implementation for advancing CID on future platform sensors and incorporation of…
Read the FY2027 plan →FY2027 planned work -Continue algorithm development for efforts toward identification of enemy targets in an actively denied ground environment (camouflage, concealment, denial and decoy conditions). -Complete bistatic SAR effort with demonstrated software integration planning for planned and potential platforms. -Continue integration of weapon integrated CID into program of record with initial planning for algorithm application to other weapon systems. -Continue efforts for on-board/off-board sensor employment to support Air-to-Ground JMAC and non-JMAC instantiations of CID on assets within Air Force planned kill-web to include multi-domain assets, demonstration of concepts. -Continue air-to-ground sensor…
FY2026 to FY2027 change FY 2027 decreases compared to FY 2026 by $0.085 million due completion of a major software integration onto platforms.
FY2026 plans — current year -Continue algorithm development for efforts toward identification of enemy targets in an actively denied ground environment (camouflage, concealment, denial and decoy conditions). -Continue bistatic SAR effort with Phase 3 to demonstrate integrated capabilities. -Continue integration of weapon integrated CID into program of record with potential for application to other weapon systems. -Continue efforts for on-board/off-board sensor employment to support Air-to-Ground JMAC and non-JMAC instantiations of CID on assets within Air Force planned kill-web to include multi-domain assets, demonstration of concepts. -Continue air-to-ground sensor feature extraction algorithm necessary for…
FY2027 planned work -Continue conduct of concept call to identify and evaluate CID technologies that advance current capability. -Evaluate modeling, simulation, and analysis of new and ongoing CID technology development. -Continue machine learning and synthetic/real data operational use; initiate targeted use of artificial intelligence (AI) within CID algorithms. -Continue planning demonstrations in relevant operational environment for study demonstrations. -Continue development of a technical roadmap for CID Technologies to inform future studies. -Continue mission engineering studies to inform CID architecture for plans and requirements.
FY2026 to FY2027 change FY 2027 decreased compared to FY 2026 by $0.903 million due to late awarding in FY26 of previous year study (FY25).
FY2026 plans — current year -Plan to continue conduct of concept call to identify and evaluate CID technologies that advance current capability. -Evaluate modeling, simulation, and analysis of new and ongoing CID technology development. -Continue machine learning and synthetic/real data operational use; initiate targeted use of artificial intelligence (AI) within CID algorithms. -Continue planning demonstrations in relevant operational environment for study demonstrations. -Continue development of a technical roadmap for CID Technologies to inform future studies. -Continue mission engineering studies to inform CID architecture for plans and requirements.