基于奇异性指数的BPSK信号细微特征分析

Because of the differences of hardware between individual communication transmitters, the waveform of process of phase shifte of BPSK signal is different. This paper used Lipschitz exponent to quantificationally characterize waveform variations of BPSK signal based on wavelet transform.According to simulation, we presented the waveform variations of phase shift process, resulting from the different filters, were difrectly reflected on Lipschitz exponent, and used the Lipschitz exponents of process of phase shift as a fine characteristic of BPSK signal. At last, the results of classification and recognition based on BP neural network prove this method is useful.