Novel Approach to Detect the Spread Spectrum Signal and Estimate Period of PN Based on Blind Source Separation
Huicheng Yang, Xiaoxue Wang, Yuan Zou, Liling Wang · 2011
The direct sequence spread spectrum (DS-SS) signal detection is a very important topic in the field of communication antagonism. An approach is proposed to detect baseband DS-SS signal with narrowband interference based on Blind Source Separation and fluctuations of autocorrelation second moment. Based on Independent Component Analysis (ICA), the noise is removed from the mixed signal first, and then DS-SS signal is detected by fluctuations of autocorrelation second moment. This paper improves the algorithm of detecting DS-SS signal by the autocorrelation second moment and analyzes the factors which impact performance of detecting, including number of data window, period of m sequence and SNR. Actual data analysis demonstrates Blind Source Separation not only can separate DS-SS signal from narrowband interference, but also improves SNR by 1dB using fluctuations of autocorrelation second moment to detect DS-SS signal when there is no other than random noise and DD-SS signal.