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2021 OES China Ocean Acoustics, COA 2021

作者： Jin, Bai Lianhui, Jia Chunxia, Meng Fengrui, Bai Science and Technology on Underwater Test and Control Laboratory Dalian China Dalian Neusoft University of Information Dalian China

ISBN: (纸本)9781728181905

The sound velocity in ice is of great significance to the acoustic propagation characteristics of ocean channels under ice cover and the acoustic characteristics of underwater targets. Freshwater ice has a uniform crystal structure under normal conditions. The freezing process of sea ice is more complicated compared to fresh water ice. The sea ice contains a lot of bubbles, brine, solid particles and other impurities. Due to the large difference in the structure and composition of ice in different states, it is very different from the common sound transmission media in the past. Therefore, in order to accurately describe the acoustic propagation characteristics of the ocean channel under the ice cover, it is necessary to measure the longitudinal sound velocity in the ice accurately. A direct method for measuring the speed of longitudinal waves in ice is studied in this paper. The propagation time of high-frequency pulses in the ice is used in this research to determine the speed of longitudinal waves. For the same piece of ice, the method of averaging multiple measurements was used to reduce the measurement error. Six tests were performed on typical ice with different structural characteristics. The six tests were the fresh water in Songhua Lake area of Jilin Province in 2019, the high mud content sea ice in the coastal area of Bohai Bay in 2020, the low mud content sea ice in Liaodong Bay area in 2021, the artificial quick-frozen sea ice and fresh water ice at -20°C, and the summer Arctic sea ice obtained in the eleventh Arctic scientific survey in 2020. The sound velocity of longitudinal waves in ice was measured at 12kHz, 25kHz, 50kHz, 75kHz, and 100kHz. The acoustic properties of ice are determined by its own state. The measurement results have certain fluctuations, because the test results were closely related to the sample test environment and test process. The measurement results of longitudinal wave sound velocity were described by the measurement mean value

关键词： underwater acoustics

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Hybrid signal fusion for target detection in distributed PA-MIMO radar systems on moving platforms

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Zhou, Dingsen Yang, Minglei Lian, Hao Greco, Maria Sabrina Gini, Fulvio Xidian University National Key Laboratory of Radar Signal Processing Shaanxi Xi'an710071 China Science and Technology on Underwater Test and Control Laboratory Dalian116013 China University of Pisa Department of Information Engineering Pisa56122 Italy

Distributed phased multiple-input multiple-output (PA-MIMO) radar systems on moving platforms combine the spatial diversity of MIMO radars with the coherent gain of phased-array radars, making them ideal for dynamic environments. However, challenges such as motion-induced channel variability, Doppler shifts, and complex parameter estimation often hinder target detection. Traditional methods like non-coherent fusion (NCF) and coherent fusion (CF) struggle to adapt to such variability, leading to suboptimal performance. In this paper, we propose a hybrid signal fusion (HSF) scheme that integrates joint space-time-phase compensation (JSTPC) with a compressed fusion network. The JSTPC module mitigates motion-induced phase errors and ensures precise alignment of received signals, while the compressed fusion network combines CF and NCF stages, leveraging their respective strengths to adaptively manage channel correlation variability. We also develop a joint parameter estimation algorithm to accurately extract direction of departure, direction of arrival, and Doppler frequency, thereby ensuring precise signal reconstruction and enhancing the detection process by estimating key parameters in real time. Theoretical analyses of detection thresholds and probabilities, derived using moment-matching techniques, further validate the reliability of the proposed scheme. Monte Carlo simulations and theoretical analyses for diverse radar configurations and channel correlation scenarios show that the proposed HSF scheme achieves 2 dB detection gain improvement over NCF. © 2025 IEEE.

关键词： Frequency estimation

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Reconstruction and Evaluation of Ship Radiated Noise Signal in Ocean Channel 4

Reconstruction and Evaluation of Ship Radiated Noise Signal ...

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4th Annual International Conference on Data Science and Business Analytics, ICDSBA 2020

作者： Meng, Chun Xia Xia, Chun Yan Li, Xiao Yuan Science and Technology on Underwater Test and Control Laboratory Dalian China Dalian Scientific Test and Control Technology Institute Dalian China

ISBN: (纸本)9781728181646

Ship radiated noise can generally be regarded as a random process that undergoes steady states, but the complexity of its generation mechanism makes its spectral characteristics different from white noise signals. Realistic simulation of the time domain signal of ship radiated noise can improve performance of acoustic equipment. In this paper, the analysis methods of the ship's radiation noise line spectrum and continuous spectrum characteristics are studied. The near-field radiation noise data of a certain type of ship under the same operating conditions is analyzed in the time-frequency domain, and the statistically significant radiation noise spectrum characteristics are obtained. The probability density function is used to generate random numbers that meet this statistical characteristic to describe the frequency spectrum of underwater radiating sound sources at various frequencies, and the Fourier synthesis method is used to reconstruct the time-domain pass characteristic of the ship's radiated noise signal under arbitrary sound velocity conditions in shallow water. Finally, the evaluation method of the radiated noise signal modeling results is studied, and the reconstructed signal is evaluated by the similarity calculation between the measured and simulated signal. The results show that the reconstructed time domain signal has higher fidelity. © 2020 IEEE.

关键词： Random processes

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Experimental Investigation on Sloshing Mitigation Effect of Floating Foam Balls 32nd

Experimental Investigation on Sloshing Mitigation Effect of ...

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32nd International Ocean and Polar Engineering Conference, ISOPE 2022

作者： Zhou, Zhimin Dai, Jierao Zhang, Chongwei Su, Peng Ning, Dezhi Science and Technology on Underwater Test and Control Laboratory the 760th Research Institute of China Shipbuilding Industry Corporation Liaoning Province Dalian China State Key Laboratory of Coastal and Offshore Engineering Dalian University of Technology Liaoning Province Dalian China

ISBN: (纸本)9781880653814

This study considers an anti-sloshing technique based on floating foam balls. Physical experiments are conducted in a rectangular tank to investigate the sloshing mitigation effect (measured by the wave height reduction factor, WHRF). Both the wave elevation and dynamic pressure in the sloshing tank are analyzed for different sizes of foam balls. It is found that floating foam balls can help reduce the sloshing violence and the corresponding pressure amplitude at the resonance condition. The sloshing mitigation effect increases with the layer number of foam balls. Meanwhile, for the sloshing tank with a fixed thickness of foam layer, smaller foam balls have a stronger sloshing mitigation effect. The sloshing mitigation effect tends to have positive correlation with the number of contacts of foam balls. © 2022 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Tanks (containers)

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Research on Feature Extraction and Recognition Method of underwater Acoustic Target Based on Deep Convolutional Network

Research on Feature Extraction and Recognition Method of Und...

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2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2020

作者： Wang, Peibing Peng, Yuan Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (纸本)9781728165202

underwater acoustic target recognition technology is an important support technology for underwater acoustic information acquisition and underwater acoustic information confrontation. Its core includes target feature extraction and classification recognition. In this paper, deep convolution neural network is applied to feature extraction and classification of underwater acoustic target signal based on LOFAR spectrum. Firstly, the extraction method and preprocessing of LOFAR spectral features are introduced. Then, the applicability of deep convolution neural network in feature extraction and LOFAR spectrum of underwater acoustic target signal is briefly analyzed. Finally, the model construction and parameter optimization method of deep convolution neural network are explained in detail. Through analysis and research, this method has good applicability in the field of underwater acoustic target recognition. © 2020 IEEE.

关键词： Feature extraction

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Research on underwater acoustic target recognition based on LOFAR spectrum and deep learning method 5

Research on underwater acoustic target recognition based on ...

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5th International Conference on Automation, control and Robotics Engineering, CACRE 2020

作者： Wang, Peibing Peng, Yuan Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (纸本)9781728198880

underwater acoustic target recognition has long been an internationally recognized problem. This paper combines the method based on LOFAR spectrogram and the deep convolutional neural network of deep learning hot spot method for underwater target radiated noise recognition, making full use of the separability information of target noise in different dimensions, and using the time spectrum chart as the depth Learn to enter data. In this paper, the basic principle and specific application process of the method are analyzed in detail, and the measured data are simulated and classified, and the simulation diagram and test results are given. The results show that the recognition rate of underwater target recognition with this method is high. © 2020 IEEE.

关键词： Convolutional neural networks

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Echo Highlight Model of underwater Target and Design of FPGA Signal Simulation Module 5

Echo Highlight Model of Underwater Target and Design of FPGA...

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5th International Conference on Communication, Image and Signal Processing, CCISP 2020

作者： Chen, Hu Fengzhen, Zhang Zhaohui, Zhang Yuan, Peng Yi, Jiang Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (纸本)9781728185897

The rapid development of FPGA provides a new platform for target signal simulation. In this paper, we first analyze the mathematical model of underwater target echo highlights, and then design a set of signal generating module based on FPGA, which can simulate the target echo signal under specific target characteristics according to the preset highlight table and copy signal. With 5° as the unit, the angle of incidence is switched between 0°-180° by using the mechanical keys. The angle can be displayed in real time through the digital tube. The output signal can be directly connected to the transducer and power amplifier to achieve a specific sound source level. Finally, the signal acquisition test of the simulation module is carried out. 37 angles in the range of 0°-180° were collected and analyzed. The distribution of echo highlights was compared with the table of highlights after matched filter. The module's performance meets the expectation. © 2020 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Experimental Study on Direction of Arrival Estimation of Acoustic Signals Based on Hyperbeam Cross Spectrum

Experimental Study on Direction of Arrival Estimation of Aco...

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2020 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2020

作者： Mingwei, Zhang Chunping, Zhai Yansen, Liu Shuwei, Che Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (纸本)9781728172019

The direction of arrival estimation(DOA) technology plays an important role in acoustic beacon fast search and rescue at sea. In this paper, the DOA resolution of the split array beam-forming is improved by using the method of Hyper Beam-Forming(HBF) cross-spectrum. Under the condition of a certain signal-to-noise ratio, HBF cross-spectrum beam-forming method based on split array can effectively improve main lob width, reduce side-lobe effect and improve the resolution of direction finding significantly. Provide an effective judgment basis for the location estimation of acoustic beacons by using the intersection area of multi-point high-precision direction finding rays and the mean intersection. In this paper, the theoretical derivation process of the proposed method is given, and the error analysis of the azimuth estimation is carried out. The simulation and experimental results show that the side-lobe can be obviously suppressed by the split array HBF cross-spectrum method, and the accuracy and reliability of the target DOA estimation can be improved. The fusion method of the intersection area of multi-ray and the intersection point of multi-ray mean can effectively reduce the acoustic beacon search radius and improve search efficiency. © 2020 IEEE.

关键词： Signal to noise ratio

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Echo signal simulation system 3

Echo signal simulation system

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3rd International Conference on Mechanical, Electric and Industrial Engineering, MEIE 2020

作者： Gao, Feng Zhang, Yang Wang, Zhenshan Li, Guijuan Science and Technology on Underwater Test and Control Laboratory Dalian China

In order to meet the demand of realistic simulation for complex target echo signal in water, the indirect method of frequency domain is employed to simulate the target echo signal in this paper. The plate element method is first used to forecast complex target echo characteristics in typical water. After generating frequency response function data, the data is imported into the echo signal simulation system. The system adopts FPGA real-time signal processing system based on PXIe bus. It receives hydrophone output signal by A/D sampling, extracts the incident acoustic signal and makes frequency domain transformation. After multiplying the transformed signal and frequency response function, scattering echo spectrum is obtained. And then the time domain transformation is made to get the time series of the echo signal. The series is loaded into the transmitting transducer by the power amplifier and the echo signal is simulated. The system has the high fidelity of the model, stable and reliable hardware system, and software system for easy operation. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Power amplifiers

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Study on the characteristics of dolphins click signal 5

Study on the characteristics of dolphins click signal

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5th International Conference on Communication, Image and Signal Processing, CCISP 2020

作者： Zhaohui, Zhang Yuan, Peng Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (纸本)9781728185897

Dolphins have a strong ability of target identification in the ocean, how to use it has become a new field of *** is mainly divided into three categories in the research of dolphin communication signals namely whistle, click and emergency signals. Dolphin Click sound is mainly used for target detection and recognition. In this paper, the research group designed a pool experiment to obtain the click signal when dolphin identify rubber bar, reef, aluminum bar and steel ball, and analyzes the signal form, frequency, spectrum change rule and other information from the perspective of time domain and time-frequency domain. The number of sine waves in click signal is analyzed when dolphins identify four kind of targets. We summarize six kinds of spectrum forms to classify the acquired acoustic signals, the probability of each spectrum form is analyzed and counted when dolphins detect and identify different *** results show that the click signal emitted by dolphins in target recognition is mainly one waveform click signal. The main energy of the frequency is concentrated at 0-200khz. © 2020 IEEE.

关键词： Signal processing

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