The invention provides a method for identifying digital modulation signals in the presence of complicated
noise. The method comprises the following steps that fraction low-order rapid independent composite analysis is conducted on an observation vector x of a received
signal, and the received
signal is divided into a transmitting
signal and Alpha stable distribution
noise; ensemble average LMD based on interpolation is conducted on the separated transmitting signal s(n), and the transmitting signal is decomposed into multiple components; the first classification feature, namely the subsection instantaneous
frequency standard deviation sigmaf of a component, is extracted, and a corresponding threshold
delta 1 is set; a second classification feature, namely subsection
instantaneous amplitude standard deviation sigmaa of the components, is extracted and a corresponding threshold
delta1 and a corresponding threshold
delta2 are set; a signal set {MSK, 2ASK, QPSK and 16
QAM} is divided into two types, namely the signal set {MSK} and the signal set {2ASK, QPSK and 16
QAM} through the threshold delta1, and signals in the signal set {2ASK, QPSK and 16
QAM} are identified through the threshold delta 2 and the threshold delta3. By the adoption of the method for identifying digital modulation signals in the presence of complicated
noise, the performance of identifying signals existing in a low-signal-to-noise-ratio environment in the presence of the Alpha stable distribution noise is high, and the stability is high.