Recent work on electronic countermeasure (ECM) technique generation employed genetic algorithm optimization methods to define simple range-gate pull-off waveforms against a generic range-tracking radar simulation. This automated approach has potential to greatly reduce technique development time which is traditionally prolonged by manual experimentation. However, it also inspires a more generalized approach to optimization with hardware-in-the-loop configurations. This work investigates and develops the underlying mathematical and empirical framework for using optimization algorithms for hardware-in-the-loop simulation and testing. Unlike other reported radar/ECM optimization simulations, this approach uses a cost function library and scoring definition to separate simulation from the optimization algorithm, and is easily adapted to hardware-in-the-loop testing. In addition, effects from electromagnetic scattering and radar receiver processing may be measured, removing the need for completely defined objective functions. Finally, this approach nicely generalizes to multiple simultaneous cost function optimization. The method is demonstrated using the wellknown range-gate pull-off technique, but is adaptable to other ECM techniques. Future efforts will investigate specific optimization algorithms for the multi-objective problem.
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