Chip Rate Estimation of DSSS Signals Based on the Morlet Wavelet Power Spectrum Method

In non-collaborative communications, the accurate estimation of the chip rate is a crucial prerequisite for blind detection and blind demodulation of direct sequence spread spectrum (DSSS) signals. However, precise estimation of the chip rate remains a major challenge, especially in low signal-to-noise ratio (SNR) conditions. To solve this problem, this paper introduces a novel approach that combines the Hilbert transform with the Morlet wavelet transform and power spectrum calculation. Additionally, we discuss how to choose an appropriate scaling factor in detail, which enhances the analysis of the signal's frequency components. Theoretical analysis and simulation results conclusively demonstrate the method's robustness and accuracy in estimating the chip rate of DSSS signals in low SNR environments.