Automatic radio-frequency environment analysis

The ability to automatically characterize all RF sources that have significant energy at a particular point in space has important applications in scientific, military, and industrial settings. Examples include automatic characterization of interference in radio astronomy, automatic signal detection and classification for military surveillance, and interference characterization for communication-system test and evaluation. Such analyses are particularly difficult when the unknown RF signals overlap in both time and frequency or when the number of possible signal types is large. In this paper we present a method of automatically detecting, characterizing, and classifying each of a number of RF sources that can spectrally and temporally overlap and that can be weak relative to the receiver noise. The method exploits the structure of higher-order statistics of manmade RF signals.