An Automatic Detection Method for Morse Signal Based on Machine Learning

In this paper, an automatic detection for time-frequency map of Morse signal is proposed base on machine learning. Firstly, a preprocessing method based on energy accumulation is proposed, and the signal region is determined by nonlinear transformation. Secondly, the feature extraction of different types of signal time-frequency maps is carried out based on the graphics. Finally, a signal detection classifier is built based on the feature matrix. Experiments show that the classifier constructed in this paper has the generalization ability and can detect the Morse signal in the broadband shortwave channel, which improve the accuracy of Morse signal detection.

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