Source Code for Power Spectral Density Estimation

This source code provides MATLAB implementations for power spectral density estimation of stationary random signals. The implementation includes two advanced spectral estimation techniques: Welch's modified periodogram method and Thomson's multitaper method. The Welch method improves upon standard periodogram techniques by dividing the signal into overlapping segments, applying a window function to each segment, computing periodograms, and averaging them to reduce variance. Key implementation considerations include selecting appropriate window lengths and overlap percentages to balance spectral resolution and estimation variance. Thomson's multitaper method employs multiple orthogonal tapers (Slepian sequences) to obtain independent spectral estimates, which are then combined to produce a more robust power spectrum estimate. This approach is particularly effective for signals with low signal-to-noise ratios. In our MATLAB implementation, the pwelch() function forms the basis for Welch's method, while the pmtm() function implements the multitaper approach. The code allows parameter customization including window size, overlap percentage, and number of tapers. Proper parameter selection based on signal characteristics is crucial for obtaining optimal spectral estimation results with minimal bias and variance. Both methods provide more accurate power spectrum estimates compared to basic periodogram techniques, enabling better understanding of signal characteristics and frequency domain properties.