In order to effectively count the changes of resident electromagnetic interference (EMI) of radio observatory sites and improve the efficiency of real-time electromagnetic environment monitoring, a method for detecting and identifying resident EMI signals based on prior information is proposed. Firstly, through signal-to-noise separation and signal energy estimation, the center frequency, polarization mode, incoming wave direction and other characteristics of permanent large signals such as mobile communication and terrestrial digital TV are extracted from the historical monitoring data of electromagnetic environment. After analyzing the fading mode of wireless signal propagation channel, the hypothesis of distribution function obeyed by the signal energy model is proposed and verified by K-S test. The K-S test method is used to obtain the distribution law obeyed by the resident signal energy, reasonably set the energy threshold and establish the signal template library. Secondly, according to the signal characteristics in the signal template library, the real-time spectrum data is tested by dual threshold energy detection and signal correlation recognition, so as to improve the accuracy of signal inspection. Finally, the fast statistics of resident signals is realized, which provides an important basis for the formulation of station site interference mitigation strategy.