@inproceedings{8a77b5759ba04dfe985887a2e404a95e,
title = "The performance of weak underwater acoustic signal detection based on passive time reversal and stochastic resonance",
abstract = "There are mainly two factors, multipath effect and strong background noise, affecting the performance of underwater weak acoustic signal detection. In this paper, to improve the performance, we propose a joint detection approach for underwater weak acoustic signal by combining the approaches of Passive Time Reversal (PTR) and Stochastic Resonance (SR). By calculating the input and output signal-to-noise ratios (SNR) theoretically, it{\textquoteright}s found that the proposed PTR-SR approach could improve the SNR of received signal, which is obtained by utilizing the multipath propagation channel and background noise simultaneously. Further, we propose a strategy to properly setting the free amplitude parameter Asr to optimize the SNR gain. Based on the Neyman-Pearson criterion, simulation results also highlight the performance of the proposed joint detection approach over single PTR approach and SR approach, especially in the circumstance of low SNR.",
keywords = "Background noise, Input-output SNR, Multipath effect, Neyman-Pearson criterion, PTR, SR",
author = "Lei Liu and Xiaohong Shen and Shilei Ma and Zhichen Zhang",
note = "Publisher Copyright: {\textcopyright} 2018 The authors and IOS Press. All rights reserved.; 4th International Conference on Fuzzy Systems and Data Mining, FSDM 2018 ; Conference date: 15-11-2018 Through 16-11-2018",
year = "2018",
doi = "10.3233/978-1-61499-927-0-572",
language = "英语",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "572--581",
editor = "Tallon-Ballesteros, {Antonio J.} and Kaicheng Li",
booktitle = "Fuzzy Systems and Data Mining IV - Proceedings of FSDM 2018",
}