A Novel Ridge Detector for Nonstationary Multicomponent Signals: Development and Application to Robust Mode Retrieval

Nils Laurent (1) , Sylvain Meignen (1)

1 CVGI - Calcul des Variations, Géométrie, Image

Time-frequency analysis is often used to study non stationary multicomponent signals, which can be viewed as the surperimposition of modes, associated with ridges in the TF plane. To understand such signals, it is essential to identify their constituent modes. This is often done by performing ridge detection in the time-frequency plane which is then followed by mode retrieval. Unfortunately, existing ridge detectors are often not enough robust to noise therefore hampering mode retrieval. In this paper, we therefore develop a novel approach to ridge detection and mode retrieval based on the analysis of the short-time Fourier transform of multicomponent signals in the presence of noise, which will prove to be much more robust than state-of-the-art methods based on the same time-frequency representation.

Keywords: AM/FM multicomponent signals; Short-time Fourier transform; Ridge detection; Mode retrieval

Domains: Signal and Image processing

Nils Laurent, Sylvain Meignen. A Novel Ridge Detector for Nonstationary Multicomponent Signals: Development and Application to Robust Mode Retrieval. IEEE Transactions on Signal Processing, 2021, 69, pp.3325-3336. ⟨10.1109/TSP.2021.3085113⟩. ⟨hal-02945707v2⟩