A focus area for SRC is the challenge of achieving spectrum dominance for military applications that employ radio frequency (RF), such as radar, electronic warfare (EW) and navigation systems. To do this, we need to limit an adversary’s use of the spectrum, secure it for friendly forces, and provide situational awareness of the electronic battlespace. Success requires a powerful, integrated framework that supports “sense, learn and adapt” capabilities, otherwise referred to as cognitive RF. In the “sense” phase of cognitive RF, an established framework allows us to automate pattern detection functions from an emitter’s semantic description for signal classification. In the “learn” phase, residual signals are then examined for discernible patterns. Once discovered, the unknown is automatically encoded within the framework and becomes a significant addition to the knowledge of the threat, thus becoming a newly learned capability. The result is an enhanced knowledge store that houses the descriptions of all previously known and recently learned emitters. In the “adapt” phase, the newly learned capability is employed for detecting the previously unknown source. We can now respond appropriately to the source of the signal. SRC has successfully developed and demonstrated this approach on both real and synthetic data sets. It has been verified for a tank-mounted, tracking/missile guidance radar, a dual-antenna air defense radar with simultaneous search/track, and a phased array air defense radar. |
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