Signal Recognition Using Multi-View Evidence and a Hierarchical Probabilistic Model Without Prior Knowledge.

This method makes it possible to accurately identify multi-class signals at signal-to-noise ratios of 0 dB and above, even without prior knowledge, by using multidimensional physical features obtained from time, frequency, and time-frequency domains; this provides a critical advantage in areas such as electromagnetic situational awareness and signal intelligence.