Power Spectrum Estimation Program with Algorithm Implementations

This power spectrum estimation program utilizes harmonic signals from power systems as input data. The implementation includes multiple high-resolution spectral estimation algorithms: Burg algorithm (for autoregressive modeling), ESPRIT algorithm (for parameter estimation via rotational invariance techniques), MUSIC algorithm (multiple signal classification for frequency estimation), MVDR algorithm (minimum variance distortionless response), Pisarenko algorithm (for harmonic retrieval), Prony algorithm (for modeling signals as sums of exponentials), modified covariance algorithm (improved autoregressive estimation), and autocorrelation algorithm (classical periodogram approach). All codes are originally developed with clear annotations referencing the source books and specific page numbers. The programs have been extensively debugged and verified for numerical accuracy and algorithmic correctness.

Additionally, the program framework supports integration of other spectrum estimation algorithms such as Bartlett's method (averaged periodograms), Welch's method (overlapping segments with windowing), and Blackman-Tukey approach (smoothed periodograms). These alternative algorithms can be selected based on specific application requirements and signal characteristics to achieve optimal estimation accuracy. The modular code structure allows for algorithm improvements and optimizations to enhance computational performance and efficiency through techniques like matrix operation optimization and parallel processing implementation.

Beyond spectrum estimation, the codebase can be extended to develop complementary power system analysis tools including frequency response analysis (using transfer function estimation), phase analysis (via cross-spectral density calculations), and harmonic distortion assessment. These analytical tools provide comprehensive insights into power system characteristics and performance metrics, enabling system optimization and improvement through quantitative signal processing approaches.

These enhancements and extended capabilities are designed to maximize the utility and application scope of the power spectrum estimation program. For technical support or further development assistance, please feel free to contact me for implementation guidance and code customization.