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Underwater Acoustic Target Recognition Using Software Defined Radio
2023 46th International Conference on Telecommunications and Signal Processing (TSP), 2023One of the important results of ship movement is acoustics noise which contains a lot of ship attributes. With developing technology, the classification of targets problem remains important. Recognition of ships is possible using ships' acoustic trace data.
İlhan, Hacı, Pehlivan, Adil Ugur
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Underwater acoustic targets recognition algorithm based on NMF
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 2020To solve the problem of low recognition rate of underwater targets for the reason of their large feature discreteness within class and high feature overlapping between classes, the underwater targets recognition algorithm based on NMF universal dictionary model (UDM) is proposed, in which, the UDM is established using the existing underwater acoustic ...
Xiaoqing Zheng +3 more
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Deep learning-based recognition of underwater target
2016 IEEE International Conference on Digital Signal Processing (DSP), 2016Underwater target recognition remains a challenging task due to the complex and changeable environment. There have been a huge number of methods to deal with this problem. However, most of them fail to hierarchically extract deep features. In this paper, a novel deep learning framework for underwater target classification is proposed. First, instead of
Xu Cao +3 more
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Underwater Target Recognition with Sonar Fingerprint
2006To recognize an underwater target precisely is always a more difficult task for the navy compared to the air force due to the complicated watery environment which is very different from the aerial circumstance. Part of the reason is that there is much more interference under the sea.
Jian Yuan, Guo-Hui Li
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Robust recognition of targets for underwater docking of autonomous underwater vehicle
2016 IEEE/OES Autonomous Underwater Vehicles (AUV), 2016Underwater docking for an autonomous underwater vehicle is important in sense that the vehicle can stop at a docking station to recharge its battery, transfer data, and can be used for launch and recovery system. To perform docking, recognizing the station through vision is important.
M. F. Yahya, M. R. Arshad
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Fuzzy logic for underwater target noise recognition
[Proceedings 1993] Second IEEE International Conference on Fuzzy Systems, 2002Underwater target noise recognition in modern sonar design is considered. The target noise is divided into five types, and their characteristics in the frequency domain are described. A fuzzy logic algorithm for passive classification is presented. An expert system based on this inference logic for target noise recognition is introduced. Some test data
J. Wang, Q. Li, W. Wei
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Intelligent Recognition of Underwater Acoustic Target Noise on Underwater Glider Platform
2018 Chinese Automation Congress (CAC), 2018The underwater acoustic target detection system based on the underwater glider platform requires the platform itself to have the ability of target automatic tracking, identification and evaluation, but the traditional methods of underwater target noise identification have strong human-computer interaction characteristics.
Zhang Shao-Kang +3 more
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Research on decision fusion in underwater target recognition
The 2nd International Conference on Information Science and Engineering, 2010Aimed at enhancing the adaptive information fusion capability of underwater target recognition in complex environment, we employed the decision fusion technology based on the Dempster-Shafer Theory. The information fusion model presented in this paper utilized neural networks and fuzzy theory, which is the basic theory for this model, to analyze the ...
null Jun Yong, null Ruo-Qian Zhu
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Underwater Target Recognition Using Artificial Fish-Swarm Algorithm
2009 Chinese Conference on Pattern Recognition, 2009In order to decrease negative effects brought by the particularity and complexity of imaging environment, and satisfy the real-time need of the underwater task, combined invariant moments are extracted as recognition features. Furthermore, an underwater target recognition system based on neural network which improved by Artificial Fish Swarm Algorithm (
He Zhang, Lei Wan, Xu-dong Tang
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Underwater Target Recognition Method Based on Convolution Autoencoder
2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), 2019Aiming at the underwater target radiated noise recognition under the limitation of low signal-to-noise ratio and small number of labeled samples, the deep learning method of convolutional autoencoder is proposed for target noise time-frequency image recognition.
Yuechao Chen, Jintao Shang
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