Aerodynamic pressure measurements are usually interpreted through statistical tools involving modal representations. The most popular approach is based on the Principal Component Analysis (PCA), which provides the theoretical basis of the well-known concept of coherent structure is derived. In order to overcome theoretical and practical limitations of PCA, alternative approaches can be formulated adapting techniques developed in the feature-recognition field to the description of pressure fields. In this sense, the Independent Component Analysis (ICA) can be conceived as an evolution of PCA in which high-order statistics are used to identify statistical independent sources; ICA has been used to solve the Blind Source Separation (BSS) problem as well as to extract features from random data. Both PCA and ICA shows severe limitations when applied to represent (and interpret) propagating phenomena such as the pressure field due to a vortex shedding and its advection by the mean flow. The explicit description of the time evolution is introduced through two techniques presented herein, Dynamic-PCA and Dynamic-ICA, and the novel concept of dynamic coherent structure is presented. The application of the above-mentioned methods is demonstrated referring to the aerodynamic pressure field measured on a bluff body immersed in a turbulent boundary layer.