Abstract
Influenced by the complexity of ocean environmental noise and the time-varying of underwater acoustic channels, feature extraction of underwater acoustic signals has always been a difficult challenge. To solve this dilemma, this paper introduces a hybrid energy feature extraction approach for ship-radiated noise (S-RN) based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) combined with energy difference (ED) and energy entropy (EE). This approach, named CEEMDAN-ED-EE, has two main advantages: (i) compared with empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN has better decomposition performance by overcoming mode mixing, and the intrinsic mode function (IMF) obtained by CEEMDAN is beneficial to feature extraction; (ii) the classification performance of the single energy feature has some limitations, nevertheless, the proposed hybrid energy feature extraction approach has a better classification performance. In this paper, we first decompose three types of S-RN into sub-signals, named intrinsic mode functions (IMFs). Then, we obtain the features of energy difference and energy entropy based on IMFs, named CEEMDAN-ED and CEEMDAN-EE, respectively. Finally, we compare the recognition rate for three sorts of S-RN by using the following three energy feature extraction approaches, which are CEEMDAN-ED, CEEMDAN-EE and CEEMDAN-ED-EE. The experimental results prove the effectivity and the high recognition rate of the proposed approach.
Highlights
Due to the complexity of ocean ambient noise and the time-varying of underwater acoustic channels, feature extraction of underwater acoustic signals has always been a difficult problem in the area of underwater acoustic signal processing [1,2]
The following section presents the theory related to CEEMDAN, energy difference (ED) and energy entropy (EE); the novel energy feature extraction approach for underwater acoustic signal is presented in Section 3; the proposed energy feature extraction approach is used to three sorts of ship-radiated noise (S-RN) signals in Section 4; the concluding remarks are made in the last section
This paper presents a hybrid energy feature extraction approach for S-RN, based on CEEMDAN, ED and EE
Summary
Ship-Radiated Noise Based on CEEMDAN Combined with Energy Difference and Energy Entropy. Received: 17 December 2018; Accepted: 27 January 2019; Published: 1 February 2019
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