Work

Hilbert–Huang Transform With Intelligent Noise Reduction for Passive SONAR Signal Processing

Year: 2025

Type: article

Abstract: Ocean science plays a key role in marine exploration, encouraging the development of new methods for analyzing underwater acoustic waves. In passive SOund NAvigation and Ranging (SONAR) signal processing for military vessel detection and classification, the predominant technique is the short-time Fourier transform (STFT). However, this spectral analysis method has time–frequency (TF) resolution limitations, impacting performance in feature extraction and vessel dynamic behavior monitoring. The Hilbert–Huang transform (HHT) is an alternative to STFT, providing a data-driven TF analysis with high resolution. However, in standard HHT algorithms, estimation accuracy degrades as noise increases. This article presents a novel algorithm for HHT that computes the HHT with intelligent noise removal (HHT-INR). The proposed method is focused on passive SONAR surveillance applications, in which the information of interest usually comprises different sinusoidal components produced by the vessels' machinery and propeller system. An intelligent system based on support vector machine detects and removes noisy IMF during the EMD estimation process. Results with simulated and experimental passive SONAR signals indicate better performance than the STFT-based analysis. The HHT-INR reduces background noise and enhances resolution for analyzing vessel parameters in time-varying scenarios. The proposed method significantly improved frequency resolution in experimental signals, achieving an average reduction in spectral width of approximately 28.5 times. In addition, there was an average increase of 87.9 dB in the signal-to-noise ratio.

Source: IEEE Journal of Oceanic Engineering

DOI: 10.1109/joe.2024.3519737

Authors: Elio Pithon Sarno Filho, Anderson Damacena Santos, Eduardo F. Simas Filho, Antonio Carlos Lopes Fernandes, José Manoel de Seixas, Natanael N. de Moura

Institutions: Universidade Federal da Bahia, Universidade Federal do Rio de Janeiro

Language: English

Topic: Underwater Acoustics Research

Subfield: Oceanography

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,645

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Fundação de Amparo à Pesquisa do Estado da Bahia