A detecting algorithm of DSSS signal based on auto — Correlation estimation
Zhaozhao Zhang, Jing Lei
Abstract
Zhaozhao Zhang, Jing Lei
Abstract
Direct Sequence Spread Spectrum (DSSS) signal has been widely used because of its low signal-to-noise ratio, strong anti-interference, low interception rate and multi-path effect. It is gradually replacing the traditional communications, and widely used in modern military and commercial communications systems. Therefore, the corresponding direct-communication communication reconnaissance technology has become an urgent problem to be solved in the field of communication reconnaissance area. In this paper, the autocorrelation characteristics of DSSS signal are analyzed and the second-order moment of autocorrelation function is used to improve the performance of DSSS signal. Upon completion of the DSSS detection, can also estimate the DSSS signal pseudo-code period, pseudo-code rate. The algorithm is suitable for low signal-to-noise ratio and has practical application value. Computer simulation results verify the feasibility and practicability of the method.
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Direct Sequence Spread Spectrum (DSSS) signal has been widely used because of its low signal-to-noise ratio, strong anti-interference, low interception rate and multi-path effect. It is gradually replacing the traditional communications, and widely used in modern military and commercial communications systems. Therefore, the corresponding direct-communication communication reconnaissance technology has become an urgent problem to be solved in the field of communication reconnaissance area. In this paper, the autocorrelation characteristics of DSSS signal are analyzed and the second-order moment of autocorrelation function is used to improve the performance of DSSS signal. Upon completion of the DSSS detection, can also estimate the DSSS signal pseudo-code period, pseudo-code rate. The algorithm is suitable for low signal-to-noise ratio and has practical application value. Computer simulation results verify the feasibility and practicability of the method.
Key concepts: Direct-sequence spread spectrum, Autocorrelation, Spread spectrum, Computer science, SIGNAL (programming language), Algorithm, Noise (video), Pseudorandom noise