Automated Generation of Electronic Warfare Libraries

The proposed Hierarchical Evolutionary Programming (H-EP) technology focuses on improving threat classification and electronic warfare battle management using the Genetic Programming (GP) optimization paradigm. The applications of the technology include: (1) on-shore emitter reference library optimization for classification performance, (2) forward deployed near real-time emitter reference library optimization for rapid adaptability, and (3) coordination of spectrum use and electronic attack tactics across multiple platforms. Leveraging the Hierarchical Emitter Library Optimization (HELO) prototype from Phase I, the Phase II program seeks to mature this technology, demonstrate its operational utility as a forward deployed capability, and illustrate improved effectiveness in both offensive and defensive electronic warfare operations. Using Lakotas Genetic Programming framework, each of these optimization problems can be solved by defining appropriate hierarchical hypotheses, fitness functions, and evolution operators. Once implemented, Lakotas GP analysis and test framework provides a formal methodology for selecting the most appropriate GP implementation and runtime parameters to solve the optimization problem within the desired time and with the desired accuracy.