A multi-radar and communication signal classification method based on clustering analysis
A communication signal and cluster analysis technology, applied in the field of communication, can solve problems such as no solution
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[0087] The recognition performance of the multi-signal classification algorithm is verified by MATLAB simulation. First, short-time Fourier transform is used to distinguish single-frequency signals from BPSK, QPSK, and 16QAM. During the simulation process, the single-frequency signal sampling frequency is set to 20MHz, the time width is 100us, the frequency is 100KHz, and the signal-to-noise ratio is 30dB. The symbol rate of the other three signals is set to 1MHz, the sampling rate is set to 200MHz, the carrier frequency is set to 10MHz, and the signal-to-noise ratio is 30dB. There are 200 training samples and 200 test samples each. After short-time Fourier transform of the four signals, the maximum frequency of each time window segment is obtained, and the mean square error of the maximum frequency is obtained. The mean square error graph of the four signals is shown in image 3 As shown, the classification threshold can be set to 0.1. In the test phase, this threshold is...
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