Blind Parameter Estimation System for Direct Sequence Spread Spectrum Signals: Carrier Frequency, Code Rate, and Code Period Detection

This research presents a blind parameter estimation system for Direct Sequence Spread Spectrum (DSSS) signals, designed to accurately detect key parameters including carrier frequency, code rate, and code period. Leveraging advanced signal processing algorithms such as cyclostationary analysis or autocorrelation-based techniques, the system processes received signals to automatically infer critical signal characteristics. Using algorithms like Fourier transform for frequency estimation and delay correlation for code period detection, the implementation involves feature extraction through time-frequency analysis and pattern recognition modules. This approach enables comprehensive analysis of DSSS signal properties, providing enhanced information and options for subsequent processing and applications. The system demonstrates strong robustness and performance, utilizing error-correction mechanisms and adaptive thresholding to ensure reliable parameter estimation even in complex channel environments. Overall, this system serves as a powerful foundation for DSSS signal research and applications, with potential extensions to multi-parameter joint estimation and real-time implementation scenarios.