Results 31 to 40 of about 4,866,384 (247)

Acoustic Shooting and Bounce Ray Method for Calculating Echoes of Complex Underwater Targets

Applied Sciences, 2022
The acoustic scattering characteristics of a target are of great significance to the design of underwater acoustic detection systems. With the improvement in underwater weapon detection ability, the precision and accuracy of underwater target echo ...
Gang Zhao, Wei Zheng, Naiwei Sun, Shen Shen, Xianyun Wu   +4 more
doaj   +1 more source

A Torpedo Target Recognition Method Based on the Correlation between Echo Broadening and Apparent Angle

Applied Sciences, 2022
As acoustic decoys can simulate the scale of the target through orderly control of the echo delay, simulated acoustic decoys have scale characteristics similar to those of the scaled target.
Zirui Wang, Jing Wu, Haitao Wang, Yukun Hao, Huiyuan Wang   +4 more
doaj   +1 more source

Underwater acoustic target recognition using attention-based deep neural network [PDF]

JASA Express Letters, 2021
Underwater acoustic target recognition based on ship-radiated noise is difficult owing to the complex marine environment and the interference by multiple targets. As an important technology for target recognition, deep-learning has high accuracy but poor
Xu Xiao, Wenbo Wang, Qunyan Ren, Peter Gerstoft, Li Ma   +4 more
doaj   +1 more source

Development of Underwater Acoustic Target Feature Analysis and Recognition Technology

, 2019
Underwater acoustic target recognition is an important supporting technology for the underwater information acquisition and countermeasure, and its core is the target feature extraction.
Shiliang, FANG, Shuanping, DU, Xinwei, LUO, Ning, HAN, Xiaonan, XU   +4 more
core   +1 more source

Underwater Target Recognition Based on Dynamic Ensemble of Random Forest

水下无人系统学报
Accurate recognition of the target is the key to attacking enemy for underwater acoustic homing weapon. A real-time target recognition method for underwater acoustic homing weapon was proposed based on dynamic ensemble selection technology.
Tao CAO, Jianjing DENG, Ling YUE, Yongsheng LI   +3 more
doaj   +1 more source

ia-PNCC: Noise Processing Method for Underwater Target Recognition Convolutional Neural Network [PDF]

, 2019
Underwater target recognition is a key technology for underwater acoustic countermeasure. How to classify and recognize underwater targets according to the noise information of underwater targets has been a hot topic in the field of underwater acoustic ...
Lei Chen, Ming He, Hongbin Wang, Lianke Zhou, Ci Chu, Jianguo Sun, Nianbin Wang   +6 more
core   +1 more source

Geometry parameters recognition method for underwater target model based on Kriging surrogate model

Zhongguo Jianchuan Yanjiu
ObjectivesUnderwater target parameter recognition can provide the basis for target classification and recognition. To this end, an underwater target parameter recognition method based on the Kriging surrogate model is proposed.
Jiang LIU, Yansen LIU, Sheng LI
doaj   +1 more source

Research on Neuro-Acoustic Human–Machine Collaborative Inter-Domain Global Attention Fusion for Underwater Acoustic Target Recognition

Journal of Marine Science and Engineering
To enhance the adaptability of current underwater acoustic target recognition technology in complex marine environments and improve the performance of human–machine collaborative operations, this study proposes a human–machine collaborative underwater ...
Jiaqi Zhang, Zhangsong Shi, Huihui Xu, Zhe Rao, Songxue Bai, Junfeng Gao   +5 more
doaj   +1 more source

Graph Embedding With Mel-Spectrograms for Underwater Acoustic Target Recognition

IEEE Journal of Oceanic Engineering
Underwater acoustic target recognition (UATR) is extremely challenging due to the complexity of ship-radiated noise and the variability of ocean environments. Although deep learning (DL) approaches have achieved promising results, most existing models implicitly assume that underwater acoustic data lie in a Euclidean space. This assumption, however, is
Sheng Feng, Shuqing Ma, Xiaoqian Zhu
openaire   +3 more sources

Adversarial Attacks in Underwater Acoustic Target Recognition with Deep Learning Models

Remote Sensing, 2023
Deep learning models can produce unstable results by introducing imperceptible perturbations that are difficult for humans to recognize. This can have a significant impact on the accuracy and security of deep learning applications due to their poorly understood interpretability.
Sheng Feng, Xiaoqian Zhu, Shuqing Ma, Qiang Lan   +3 more
openaire   +2 more sources