Uma contribuição à análise espectral de sinais estacionários e não estacionários

Abstract

This dissertation aims at discussing solutions to deal with spectral analysis of stationary and non-stationary processes for frequency estimation, power spectral density estimation and spectral monitoring applications. The frequency estimation techniques are assessed through computer simulations. The proposed technique for frequency estimation is based on warped discrete Fourier transform outperforms other techniques, achieving the Cramer-Rao Bound for a wide range of signal to noise ratio. Regarding the power spectral density estimation, the proposed Hartley Multitaper Method shows similar performance, in terms of variance of estimates and polarization spectrum; however, it can simplify the implementation complexity. The introduced spectrum sensing technique is based on quanta de nition and the diversity o ered by the signals acquired from the electric power grids and the air. Based on computer-generation data and those one obtained during a measurement campaign, which one in this thesis is evaluated using synthetic signals, generated by computer, as well as measurement data of the spectrum. The numerical results show that the proposed technique outperforms a previous technique and can attain the very detection ratio and the very low false alarm when the diversity yielded by electric power grid and air is exploited.