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Underwater Acoustic Target Recognition: A Combination of Multi-Dimensional Fusion Features and Modified Deep Neural Network

1
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
2
College of Computer Science and Technology, Harbin Institute of Technology, Harbin 518000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1888; https://doi.org/10.3390/rs11161888
Received: 1 July 2019 / Revised: 4 August 2019 / Accepted: 8 August 2019 / Published: 13 August 2019
(This article belongs to the Section Ocean Remote Sensing)
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Abstract

A method with a combination of multi-dimensional fusion features and a modified deep neural network (MFF-MDNN) is proposed to recognize underwater acoustic targets in this paper. Specifically, due to the complex and changeable underwater environment, it is difficult to describe underwater acoustic signals with a single feature. The Gammatone frequency cepstral coefficient (GFCC) and modified empirical mode decomposition (MEMD) are developed to extract multi-dimensional features in this paper. Moreover, to ensure the same time dimension, a dimension reduction method is proposed to obtain multi-dimensional fusion features in the original underwater acoustic signals. Then, to reduce redundant features and further improve recognition accuracy, the Gaussian mixture model (GMM) is used to modify the structure of a deep neural network (DNN). Finally, the proposed underwater acoustic target recognition method can obtain an accuracy of 94.3% under a maximum of 800 iterations when the dataset has underwater background noise with weak targets. Compared with other methods, the recognition results demonstrate that the proposed method has higher accuracy and strong adaptability. View Full-Text
Keywords: multi-dimensional fusion features; gaussian mixture model; deep neural network; underwater acoustic target recognition multi-dimensional fusion features; gaussian mixture model; deep neural network; underwater acoustic target recognition
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wang, X.; Liu, A.; Zhang, Y.; Xue, F. Underwater Acoustic Target Recognition: A Combination of Multi-Dimensional Fusion Features and Modified Deep Neural Network. Remote Sens. 2019, 11, 1888.

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