RF Spectrum Situational Awareness (SSA) and Integrated Sensing & Communications (ISAC)
Spectrum is becoming ever-more congested and contested. Detecting, identifying and tracking of RF emitters of interest are of interest in terrestrial, aerial as well as space environments. Combined statistical signal processing, deep learning, and artificial intelligence approaches show great promise in achieving desired accuracies and latencies. The emerging focus on integrated sensing and communications offers an opportunity to explore new SIGINT and SSA methods that do not require separate dedicated networks. The expansion into mm-wave regime can particularly be interesting due to the potential for antenna arrays made of large numbers of elements that provide higher localization abilities.