SBIR-STTR Award

Adversary radar jamming capability will greatly increase in the near future. Improvements in radio frequency (RF) hardware, especially in solid state RF electronics, will lead to improved jammer capability with reduced size, weight, and power requirements. Moreover, improvements in embedded computer systems will give jammers access to powerful machine learning and artificial intelligence algorithms to improve their effectiveness. will challenge current and future electronic protection systems. A strategy to mitigate the capability of cognitive jammers (e.g., sophisticated, AI-driven jammers that reacts to measured radar emissions and measure their own effectiveness) is to attempt to model and exploit the decision logic used by the jammers to select electronic protection techniques which mitigate the jammer effects. Vadum will develop the Adversary Logic Exploitation System (ALES) to probe a cognitive jammer system in order to model the jammer decision logic. ALES will use the modeled decision logic to schedule subsequent radar waveforms which both produce the information required by the radar and limit the effect of electronic attack on the radar system. The ALES algorithms will analyze incoming signals and segregate out the likely jamming signals. Changes in radar behavior which drive changes in jammer behavior are saved in a persistent data structure (the Jammer Behavior Object or JBO) and analyzed. Based on the inferred understanding of the jammer behavior, subsequent radar waveforms which avoid the effects of the likely electronic attack will be scheduled. ALES will identify and schedule both electronic protection techniques and probing waveforms to not only protect the radar, but to gain additional information about the jammer. Vadum will develop the ALES algorithms in an in-house modeling and simulation environment which supports concurrent experimentation and development of algorithm prototypes and production of software versions of those same algorithms. The Phase I effort will prove out the ALES concept sufficiently to support additional Phase II research focused on improving ALES performance by further algorithm development and characterization along with the potential inclusion of algorithms and architectures from other Vadum Cognitive Electronic Warfare programs. The Phase II program will also increase the maturity of the algorithms themselves through increased testing fidelity to support eventual Phase III transition decisions.

Benefit:
Vadum will prototype the Adversary Logic Exploitation System (ALES) algorithms whose chief benefit will be characterization and exploitation of cognitive jammer decision logic. This research will quantify the art of the possible for decision logic characterization (DLC) as an electronic protection strategy. The project will also determine the capabilities and limitations of DLC and inform the types of tactical situations in which DLC might be applicable. The process of testing ALES will also investigate the utility of potential data stores (i.e., the Jammer Behavior Object or JBO) as an enabler for distributed (multi-ship to force level) cognitive electronic warfare and data transmission back to military and intelligence analysts. The Phase I proof-of-concept effort will determine the feasibility of exploiting unknown jammer decision logic and the Phase II technology maturation program will increase the technology readiness level of the algorithms through both performance improvements and testing. Commercialization of the ALES algorithms will begin within the U.S. Navys NAVAIR community. Vadum will both work with the Government and leverage existing contacts within advanced electronic warfare groups within prime contractors such as Northrup Grumman, Raytheon, and Leidos to search for transition partners and organizations within NAVAIR. As the ALES technology matures, commercialization will proceed to the broader U.S. Navy community, including to sensor and electronic warfare development organizations such as PEO IWS 2.0. Though broader commercialization ALES will be restricted to Department of Defense customers, the potential customer base consists of any organization with a need to protect radar systems against increasingly sophisticated jammers; almost every radar system has this need. Outside of the U.S. Navy, the largest potential customer base is the U.S. Air Force, as almost every aircraft supported by the Air Force has a radar which must mitigate complex jammers. Terrestrial and airborne U.S. Army systems also represent a potential market for ALES technology. Working with the Government together with prime contractors and integrators listed above, Vadum will identify the proper organizations within the Air Force and Army which may benefit from ALES and develop specific marketing plans accordingly.

Keywords:
Electronic Protection, Electronic Protection, Decision Characterization, Cognitive Electronic Warfare, Cognitive Jammer, Cognitive Electronic Protection

Vadum will continue research into cognitive electronic protection capability development by extending the Adversary Logic Exploitation System (ALES) algorithms developed in Phase I. The objectives of the Phase II research are to more fully explore both the technical capabilities and tactical implementations of ALES. The Phase I effort demonstrated the utility of the ALES concept of modeling adversary decision logic in order to exploit that logic to support electronic protection decisions. The Phase II program will extend this work to improve and characterize the two critical components of the ALES system (Decision Logic Characterization and Radar Waveform Selection) and to evaluate potential implementation impacts of the ALES system. The result of the Phase II research and development effort will be a comprehensive set of tested jammer emitter decision logic characterization algorithms driving blue force electronic protection decisions.

Benefit:
ALES will provide novel algorithms for electronic protection against cognitive jammers, addressing the U.S. Navys operational gap seeking to maintain electronic protection capabilities in dynamic EW environments with adaptively evolving threats. As enemy jammers sense their environment and adaptively learn cognitive jamming behaviors, there is a similar need for blue-force intelligent radar systems to sense their environments and develop appropriate countermeasures, on-the-fly. The ALES algorithms offer an ability to probe a cognitive adversarial radars sense-learn-adapt loop to understand the logic driving the jammers decision-making processes based on its responses in a dynamically changing tactical environment. ALES will provide the Navy a functional capability to help inform the process of defining cognitive electronic threat requirements via probing, characterizing, and aiding the exploitation of adversarial cognitive jammers. ALES capabilities are relevant to Naval Air Systems Command (NAVAIR) elements, with the ALES market consisting of any radar system which will have future requirements for cognitive electronic protection. Vadum anticipates that such a requirement will be applicable to a wide variety of deployed and developmental systems. Other uses of the ALES algorithms include transitions to other U.S. Navy radar assets, most notably surface RF sensors and electronic warfare packages. As ALES represents the next evolution of electronic protection technology applicable to a wide range of RF systems, technology commercialization outside of the Navy, including to Army air and missile defense assets (e.g., PATRIOT and THAAD weapon systems), to Air Force radar systems, and even foreign military sales for aircraft, IADS, and other applications, like the Armys Future Vertical Lift (FVL) program, is possible in the future. The market for such applications will be evaluated after successful transition inside of the NAVAIR and U.S. Navy communities. ALES has potential application for commercial products. The core ALES concept, which involves intelligent probing and characterization of cognitive adversarial systems, has transferable components to other rapidly evolving communities such as cyber security and web-based applications, which are cognitive in nature.

Keywords:
cognitive, remote sensing, Sensors, Countermeasures, Cognitive Sensor System, adaptivity, Radar