Detection and Parameter Estimation of Spread Spectrum Signals

Our method for detecting and estimating parameters of spread spectrum signals using MATLAB demonstrates enhanced detection performance in low signal-to-noise ratio environments. The implementation involves cross-correlation techniques between received signals and known spreading codes, followed by peak detection algorithms to identify signal presence and estimate key parameters. These parameter estimation results enable further analysis to extract additional information about spread spectrum signal characteristics. Through spectral analysis and statistical processing of correlation outputs, we can comprehensively study the properties and performance of spread spectrum signals. This approach holds significant value for spread spectrum signal analysis and processing applications, particularly in communication systems requiring robust signal detection in noisy conditions. The MATLAB implementation typically utilizes functions like xcorr() for correlation computation and findpeaks() for parameter extraction, with threshold-based decision making for reliable detection outcomes.