Modern threat radar employs increasing levels of signal waveform agility in order to defeat electronic warfare (EW) systems; consequently, Helios is developing machine learning algorithms to detect agile emitters. These algorithms operate with or without emitter libraries, without just focusing on new signals outside those libraries. These algorithms correctly identify agile emitter pulses as originating from a single emitter, without fragmenting them into multiple unknown emitters. Helios machine learning algorithms build a database of new emitters. Helios has verified EW machine learning using state-of-the-art pulse densities, and developed a cost-effective solution through compatibility with Navy provided Interface Design Descriptions. Helios seeks a development contract to integrate these algorithms in electronic support measures (ESM) programs of record such as AN/SLQ-32, AN/BLQ-10, and EA-18G Next Generation Jammer.