This application relates to the field of
radar signal processing technology, and in particular to a
radar interference identification method based on multi-domain feature association and
fingerprint tracing. The method includes: digitally channelizing the received
radar signal using a
polyphase filter bank, decomposing it into multiple
narrowband sub-channels, and selecting effective sub-channels; extracting macroscopic features from the outputs of the effective sub-channels to construct high-dimensional feature vectors; inputting the high-dimensional feature vectors into a pre-trained
random forest classification model for initial interference pattern judgment to obtain preliminary judgment results; if the preliminary judgment result is deceptive interference and the
signal-to-
noise ratio of the effective sub-channels is higher than a preset
fingerprint extraction threshold, then extracting microscopic features from the outputs of the effective sub-channels to construct microscopic
fingerprint vectors; performing fine analysis of the pulse
leading edge fingerprint based on the microscopic fingerprint vectors to obtain secondary fingerprint analysis results; and combining the preliminary judgment results and the secondary fingerprint analysis results to obtain the final identification result used to characterize the interference pattern and the identity of the interference source.