Signal Detection and Parameter Estimation of Low SNR Direct Sequence Spread Spectrum Signal

Abstract

In order to realize the “ blind ” detection and parameter estimation of direct sequence spread spectrum signals under low signal-to-noise ratio (SNR) conditions, a direct sequence spread spectrum signal denoising algorithm based on wavelet packet-energy detection is proposed, which can significantly improve the SNR. Combining the wavelet packet denoising algorithm, the improved cyclic spectrum method, quadratic spectrum method and delay multiplication method, the accurate “ blind ” parameter estimation of binary phase shift keying / direct sequence spread spectrum (BPSK / DSSS) signal carrier frequency, spreading code period and spreading code rate can be realized under the condition of low SNR. The simulation results show that the proposed algorithm can realize the detection and parameter estimation of BPSKIDSSS signals more effectively.