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Cooperative and Coordinated Decentralized Warfare in Disconnected, Intermittent, Limited bandwidth (DIL) Environments

Description:

TECHNOLOGY AREA(S): Electronics, 

OBJECTIVE: Investigate and demonstrate an algorithmic approach to achieve cooperation and coordinated activity by a decentralized group of electronic warfare (EW) actors within a disconnected, intermittent, limited bandwidth (DIL) environment. 

DESCRIPTION: Future operations within highly contested environments will drive the need for networks of systems able to rapidly adapt and respond to changing conditions, such as distributed EW systems for platform survivability. The intent is to field the EW systems onto Air Launched Effects (ALE) aerial vehicles, to enhance the capability of future aviation platforms to achieve dis-integrating effects through operating as a team with other manned and unmanned platforms to penetrate into the Deep Maneuver Area. The desired EW payload capabilities of the ALE include decoy and disruptive radio frequency electronic attack as well as passive and active threat detect, identify, locate, and report (DILR) electronic support. In order to accomplish these diverse missions within the Anti-Access and Area Denial (A2AD) environment, it is expected that these capabilities may reside on multiple different payloads. Novel methods of decentralized control of the EW payload behavior sets will be required for operation within the DIL environment enabling the individual EW system actors to infer the behavior of the other actors within the network. Example missions include, but are not limited to, unmanned aircraft stand-in/stand-off jamming for aided survivability of manned aircraft, unmanned aircraft penetration and suppression of IADS to enable lethal effects and manned aircraft stand-in/self protect jamming. 

PHASE I: Define a set of notional operational scenarios for implementing the EW behavior sets of the representative actors. Determine the global optimum for each scenario through optimizing the behavior of the actors for each scenario in a preplanned manner within a permissive communications environment. 

PHASE II: Develop a set of algorithms to optimize the behavior of the EW actors in dynamic scenarios within a DIL environment. The algorithm needs to enable adaptation of actor behavior to changes in the optimization objective, resources and/or constraints of the EW actors, and the number and/or distribution of actors. Evaluate the performance of the algorithm across a variety of scenario permutations within a DIL environment. 

PHASE III: Algorithms developed and tested during Phase II can be directly applied to future technology demonstrators to enable resilient operation of decentralized EW actors within dynamically changing operational scenarios under DIL conditions. 

REFERENCES: 

1: TRADOC Pamphlet 525-3-1

KEYWORDS: Fratricide Mitigation, Resiliency, Autonomous Agents, Artificial Intelligence 

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