Information and Diagnostics Systems

Spectral Density Bias Estimation for Periodically Non-Stationary Random Processes

Roman Khmil1,2, Roman Yuzefovych1,2
1. Karpenko Physico-mechanical Institute of NAS of Ukraine
2. Lviv Polytechnic National University, Ukraine

https://doi.org/10.15407/msse2025.01.252

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Keywords

periodically non-stationary random process; instantaneous spectral density; spectral component.

Abstract

Correlogram‐based estimation of the instantaneous spectral density of periodically non‑stationary random processes is investigated for both continuous and discrete signals derived using coherent covariance methods. Expressions for the asymptotic bias and variance were obtained, first‑ and second‑order aliasing effects are examined. Proposed models were applied to treaty of the amplitude‑ and phase‑modulated signals, simulated and real time‑series examples for obtaining spectral‐density and cyclic‐components estimations.

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