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Frontiers of Information Technology & Electronic Engineering >> 2021, Volume 22, Issue 7 doi: 10.1631/FITEE.2000181

A data-driven method for estimating the target position of low-frequency sound sources in shallow seas

Affiliation(s): School of Mechanical and Automobile Engineering, Qingdao University of Technology, Qingdao 266000, China; Institute of Oceanographic Instrumentation, Shandong Academy of Sciences, Qingdao 266000, China; less

Received: 2020-04-20 Accepted: 2021-07-20 Available online: 2021-07-20

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Abstract

Estimating the target position of low-frequency sound sources in a environment is difficult due to the high cost of hydrophone placement and the complexity of the propagation model. We propose a compressed (C-RNN) model that compresses the signal received by a into a dynamic sound intensity signal and compresses the target position of the sound source into a GeoHash code. Two types of data are used to carry out prior training on the , and the trained network is subsequently used to estimate the target position of the sound source. Compared with traditional mathematical models, the C-RNN model functions independently under the complex sound field environment and terrain conditions, and allows for real-time positioning of the sound source under low-parameter operating conditions. Experimental results show that the average error of the model is 56 m for estimating the target position of a low-frequency sound source in a environment.

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