Electromagnetic interference identification method and system based on LSTM neural network

The invention discloses an electromagnetic interference identification method and system based on an LSTM neural network, and the method comprises the steps: building a test evaluation system which comprises a certain project radar seeker model, a target signal simulation system, an electronic interference simulation system and an antenna horn. By outputting various interference signals such as analog signals of different targets, distance pull-type false target interference signals, speed pull-type false target interference signals, suppressing noise interference signals and the like, a combat scene in which a radar seeker intercepts and tracks analog target signals under complex electromagnetic conditions is simulated. The method is simple to implement, can be quickly transplanted to an anti-interference model of the radar seeker, improves the accuracy of identifying different types of electromagnetic interferences, and solves the problem that an existing seeker anti-interference model does not have univers