details on advanced topics that areusually presented in scattered sources throughout theliterature.The theoretical principles necessary for the understanding ofspectral analysis are discussed in the first four chapters:fundamentals, digital signal processing, estimation in spectralanalysis, and time-series models.An entire chapter is devoted to the non-parametric methods mostwidely used in industry.High resolution methods are detailed in a further four chapters:spectral analysis by stationary time series modeling, minimumvariance, and subspace-based estimators.Finally, advanced concepts are the core of the last four chapters:spectral analysis of non-stationary random signals, space timeadaptive processing: irregularly sampled data processing, particlefiltering and tracking of varying sinusoids.Suitable for students, engineers working in industry, and academicsat any level, this book provides a rare complete overview of thespectral analysis domain.

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