Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9520012
Shuping Lu, Yang Chen, Fangxiang Chen, Feng Ding, Ranwei Li
This paper proposes a novel detection and tracking algorithm to improve the performance of continuous tracking of submarine for multistatic sonar systems. The algorithm focuses on a centralized fusion architecture and a cognitive closed loop. In the following trail of submarine, the future trajectory of the submarine and its echo intensity for different transmit-receive combinations are roughly predicted, where the target echo model is assumed to be a priori. These predicted echo intensity is fed back to the frontend detection and tracking processes. Then the proposed algorithm could adaptively adjust the key parameters of the centralized fusion rule. Moreover, the track management strategy is also adjusted based on the feedback information. At the beginning of another cycle after tracking, the future trajectory and the echo intensity of the target are predicted again. We use numerical simulations to evaluate the behavior of the proposed algorithm. It is demonstrated that the cognitive approach achieves a better performance of continuous tracking compared with the conventional non-cognitive method in terms of track probability of detection and track fragmentation rate.
{"title":"Cognitive Continuous Tracking Algorithm for Centralized Multistatic Sonar Systems","authors":"Shuping Lu, Yang Chen, Fangxiang Chen, Feng Ding, Ranwei Li","doi":"10.1109/COA50123.2021.9520012","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9520012","url":null,"abstract":"This paper proposes a novel detection and tracking algorithm to improve the performance of continuous tracking of submarine for multistatic sonar systems. The algorithm focuses on a centralized fusion architecture and a cognitive closed loop. In the following trail of submarine, the future trajectory of the submarine and its echo intensity for different transmit-receive combinations are roughly predicted, where the target echo model is assumed to be a priori. These predicted echo intensity is fed back to the frontend detection and tracking processes. Then the proposed algorithm could adaptively adjust the key parameters of the centralized fusion rule. Moreover, the track management strategy is also adjusted based on the feedback information. At the beginning of another cycle after tracking, the future trajectory and the echo intensity of the target are predicted again. We use numerical simulations to evaluate the behavior of the proposed algorithm. It is demonstrated that the cognitive approach achieves a better performance of continuous tracking compared with the conventional non-cognitive method in terms of track probability of detection and track fragmentation rate.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121116316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9519859
Xin Liu, Hao Zhang
The underwater acoustic positioning system is the mainstream of current underwater navigation positioning. Ultra-short baseline underwater acoustic positioning is one of its main methods. It has the characteristics of high accuracy, small baseline size, and convenient use. This paper designs a preprocessing system for ultra-short baseline positioning, which realizes the acquisition and A/D conversion of real-time analog signals, and performs digital filtering and sliding related processing on the FPGA platform. This article takes the SOPC system as the core, buffers the real-time signals of multiple channels, and uses the overlap preservation method to perform sliding-related segmentation processing on the buffered signals, including FFT transform, signal mixing, and IFFT transform. The results are proofread and sent into the DSP. This system implements the algorithm part through FPGA, which greatly reduces the burden on the DSP and allows the DSP more time to process other parts.
{"title":"Design and Implementation of Preprocessing Unit of FPGA-based Ultra-short Baseline Positioning System","authors":"Xin Liu, Hao Zhang","doi":"10.1109/COA50123.2021.9519859","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9519859","url":null,"abstract":"The underwater acoustic positioning system is the mainstream of current underwater navigation positioning. Ultra-short baseline underwater acoustic positioning is one of its main methods. It has the characteristics of high accuracy, small baseline size, and convenient use. This paper designs a preprocessing system for ultra-short baseline positioning, which realizes the acquisition and A/D conversion of real-time analog signals, and performs digital filtering and sliding related processing on the FPGA platform. This article takes the SOPC system as the core, buffers the real-time signals of multiple channels, and uses the overlap preservation method to perform sliding-related segmentation processing on the buffered signals, including FFT transform, signal mixing, and IFFT transform. The results are proofread and sent into the DSP. This system implements the algorithm part through FPGA, which greatly reduces the burden on the DSP and allows the DSP more time to process other parts.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125929425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the serious and complicated noise in the shallow sea environment, the received signal obtained by the hydrophone is disturbed by the noise to a large extent. It has a low signal-to-noise ratio (SNR), which leads to problems such as difficulty in processing the underwater acoustic signal. To solve this problem, to more effectively remove the ocean noise in the useful signal, a denoising method based on sparse decomposition and dictionary learning is adopted. First, a complete Discrete Cosine Transform (DCT) dictionary is randomly constructed. Then the orthogonal matching pursuit (OMP) is used to represent the noisy underwater acoustic signal sparsely, the method of optimal directions (MOD) and K-singular value decomposition algorithm (K-SVD) are used to update the complete DCT dictionary respectively. According to the updated new dictionary and sparse coefficients, the underwater acoustic signal is reconstructed, and the ocean noise is removed. By denoising the different form of simulated signals with different SNRs, the results show that two methods can remove various noises mixed in the underwater acoustic signal effectively and retain the signal details while denoising. The SNR gain can reach about 20dB.
{"title":"Low-frequency Underwater Acoustic Signal Denoising Method in the Shallow Sea with a Low Signal-to-noise Ratio","authors":"Yaowen Wu, Chuanxi Xing, Dongyu Zhang, Lixiang Xie","doi":"10.1109/COA50123.2021.9520031","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9520031","url":null,"abstract":"Due to the serious and complicated noise in the shallow sea environment, the received signal obtained by the hydrophone is disturbed by the noise to a large extent. It has a low signal-to-noise ratio (SNR), which leads to problems such as difficulty in processing the underwater acoustic signal. To solve this problem, to more effectively remove the ocean noise in the useful signal, a denoising method based on sparse decomposition and dictionary learning is adopted. First, a complete Discrete Cosine Transform (DCT) dictionary is randomly constructed. Then the orthogonal matching pursuit (OMP) is used to represent the noisy underwater acoustic signal sparsely, the method of optimal directions (MOD) and K-singular value decomposition algorithm (K-SVD) are used to update the complete DCT dictionary respectively. According to the updated new dictionary and sparse coefficients, the underwater acoustic signal is reconstructed, and the ocean noise is removed. By denoising the different form of simulated signals with different SNRs, the results show that two methods can remove various noises mixed in the underwater acoustic signal effectively and retain the signal details while denoising. The SNR gain can reach about 20dB.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115090318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9520009
Jin Huang, Yu Luo, Yanyi Li, Jian-gen Shi, Xu Zheng, Jingjing Wang
In marine mapping, the sound speed profile (SSP) is an essential parameter. The SSP reflects the characteristics of the ocean sound field’s vertical structure. Furthermore, analyzing the SSP has an important significance on the propagation of underwater sound signals. The empirical orthogonal function (EOF) can extract the SSP data’s main features. It is widely used in SSP fitting and other applications. In this paper, the studying area is 116°~117°E,18°~19°N in the South China Sea. Using the Argo data from 2010 to 2020, this paper first visually analyzes SSP, carries out the EOF’s analysis, and then elaborates the basic EOF principle. It confirms that the EOF has a good application value for the South China Sea, and the first sixth order function can accurately describe the sound speed profile. Then this paper analyzed the EOF’s temporal function. The study found that the third mode of temporal function strongly connects with the ocean’s climate condition. And the two severe fluctuations in 2010 and 2014 have a strong relationship with the typhoon passage. In other words, the degree of extreme fluctuations is positively correlated with typhoon intensity. In brief, understanding the SSP’s temporal pattern is beneficial for applying various engineering scenarios. It can improve the accuracy of sound speed correction of marine acoustic instruments, while the study of marine climate environment has an important role.
{"title":"Analysis of Sound Speed Profile in the South China Sea based on Empirical Orthogonal Function Algorithm","authors":"Jin Huang, Yu Luo, Yanyi Li, Jian-gen Shi, Xu Zheng, Jingjing Wang","doi":"10.1109/COA50123.2021.9520009","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9520009","url":null,"abstract":"In marine mapping, the sound speed profile (SSP) is an essential parameter. The SSP reflects the characteristics of the ocean sound field’s vertical structure. Furthermore, analyzing the SSP has an important significance on the propagation of underwater sound signals. The empirical orthogonal function (EOF) can extract the SSP data’s main features. It is widely used in SSP fitting and other applications. In this paper, the studying area is 116°~117°E,18°~19°N in the South China Sea. Using the Argo data from 2010 to 2020, this paper first visually analyzes SSP, carries out the EOF’s analysis, and then elaborates the basic EOF principle. It confirms that the EOF has a good application value for the South China Sea, and the first sixth order function can accurately describe the sound speed profile. Then this paper analyzed the EOF’s temporal function. The study found that the third mode of temporal function strongly connects with the ocean’s climate condition. And the two severe fluctuations in 2010 and 2014 have a strong relationship with the typhoon passage. In other words, the degree of extreme fluctuations is positively correlated with typhoon intensity. In brief, understanding the SSP’s temporal pattern is beneficial for applying various engineering scenarios. It can improve the accuracy of sound speed correction of marine acoustic instruments, while the study of marine climate environment has an important role.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115243535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9520064
Ni Haiyan, W. Wenbo, Zhao Meng, Ren Qunyan, Ma Li
Supervised classification algorithms are often used for marine noise classification. However, limited by insufficient labeled samples, the performance of the supervised classification method is typically influenced. To alleviate the limitations of insufficient labeled samples, in this paper, a semi-supervised noise classification method based on an auto-encoder (AE) has been proposed using radiated noise of four kinds of ships. This method takes a two-step training process, including unsupervised pre-training and supervised fine-tuning, making full use of unlabeled data and limited labeled data, respectively, which reduces reliance on label information for noise classification. The performance of this method is compared with traditional backpropagation neural networks (BPNN) and support vector machines (SVM). Experimental data analysis demonstrates that the semi-supervised noise classification method has improved the accuracy with different amounts of labeled samples, especially when labeled samples are relatively rare.
{"title":"Semi-Supervised Noise Classification Based on Auto-Encoder","authors":"Ni Haiyan, W. Wenbo, Zhao Meng, Ren Qunyan, Ma Li","doi":"10.1109/COA50123.2021.9520064","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9520064","url":null,"abstract":"Supervised classification algorithms are often used for marine noise classification. However, limited by insufficient labeled samples, the performance of the supervised classification method is typically influenced. To alleviate the limitations of insufficient labeled samples, in this paper, a semi-supervised noise classification method based on an auto-encoder (AE) has been proposed using radiated noise of four kinds of ships. This method takes a two-step training process, including unsupervised pre-training and supervised fine-tuning, making full use of unlabeled data and limited labeled data, respectively, which reduces reliance on label information for noise classification. The performance of this method is compared with traditional backpropagation neural networks (BPNN) and support vector machines (SVM). Experimental data analysis demonstrates that the semi-supervised noise classification method has improved the accuracy with different amounts of labeled samples, especially when labeled samples are relatively rare.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122320561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9519906
Yankun Chen, Weiping Wang, Yinian Liang, Defu Zhou, Chao Dong, Jie Li
With the continuous development of offshore engineering, major offshore projects develop rapidly. During the development of offshore engineering, different degrees of noise will be generated, and the man-made noise can have harmful effects on marine mammals. Currently, The researchers usually use Passive Acoustic Monitoring(PAM) method to monitor the marine mammals. However, it is impossible to acquire, monitor and analyze the sound of marine mammals in real time and lack of comprehensive information of marine mammals monitoring, and the data analysis and study of vocalization rules can only be carried out after data collection is completed and equipment is recovered. Therefore, this paper proposes a real-time automatic detection and classification technology to monitor targeted marine mammals efficiently and continuously timely in offshore engineering areas.
{"title":"Real-time Detection and Classification for Targeted Marine Mammals","authors":"Yankun Chen, Weiping Wang, Yinian Liang, Defu Zhou, Chao Dong, Jie Li","doi":"10.1109/COA50123.2021.9519906","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9519906","url":null,"abstract":"With the continuous development of offshore engineering, major offshore projects develop rapidly. During the development of offshore engineering, different degrees of noise will be generated, and the man-made noise can have harmful effects on marine mammals. Currently, The researchers usually use Passive Acoustic Monitoring(PAM) method to monitor the marine mammals. However, it is impossible to acquire, monitor and analyze the sound of marine mammals in real time and lack of comprehensive information of marine mammals monitoring, and the data analysis and study of vocalization rules can only be carried out after data collection is completed and equipment is recovered. Therefore, this paper proposes a real-time automatic detection and classification technology to monitor targeted marine mammals efficiently and continuously timely in offshore engineering areas.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122326177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9519854
Jikang Li, Desen Yang, Guangzhi Chen
The wake generated by the underwater structure can evolve into a wake vortex with a special flow structure, resulting in a change in the speed of sound distribution, which has an important impact on the propagation of parametric array in the ocean and causes fluctuations in the sound field. The difference-frequency sound wave generated by the parametric array is the core of the parametric array technology. The study of the difference-frequency sound field distribution characteristics is the basis for the development of the parametric array technology and the theory of the interaction of sound waves. The frequency domain algorithm is used to calculate and analyze the nonlinear acoustic scattering characteristics of the underwater vortex field and explore the nonlinear acoustic scattering characteristics of the wake field of a cylindrical structure under the conditions of different moments and Mach number. The results show that the spatial directivity of the nonlinear acoustic scattering field of the wake vortex will cause the directivity of the parametric acoustic field to shift. The difference-frequency wave becomes concave and convex on the opposite sides of the parabolic axis and the wave energy is focused and scattered. The focus will cause the amplitude of the wave to increase and decrease accordingly. The main lobe offset will increase as the flow velocity increases.
{"title":"Study on the Acoustic Scattering Characteristics of the Parametric Array in the Wake Field of Underwater Cylindrical Structures","authors":"Jikang Li, Desen Yang, Guangzhi Chen","doi":"10.1109/COA50123.2021.9519854","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9519854","url":null,"abstract":"The wake generated by the underwater structure can evolve into a wake vortex with a special flow structure, resulting in a change in the speed of sound distribution, which has an important impact on the propagation of parametric array in the ocean and causes fluctuations in the sound field. The difference-frequency sound wave generated by the parametric array is the core of the parametric array technology. The study of the difference-frequency sound field distribution characteristics is the basis for the development of the parametric array technology and the theory of the interaction of sound waves. The frequency domain algorithm is used to calculate and analyze the nonlinear acoustic scattering characteristics of the underwater vortex field and explore the nonlinear acoustic scattering characteristics of the wake field of a cylindrical structure under the conditions of different moments and Mach number. The results show that the spatial directivity of the nonlinear acoustic scattering field of the wake vortex will cause the directivity of the parametric acoustic field to shift. The difference-frequency wave becomes concave and convex on the opposite sides of the parabolic axis and the wave energy is focused and scattered. The focus will cause the amplitude of the wave to increase and decrease accordingly. The main lobe offset will increase as the flow velocity increases.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114042651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9519929
Zhou Chunkai
Due to the rapid development of submarine cable engineering, there is not only crossover between submarine cables, but also overlapping of different types of buried submarine cables, which causes serious interference to the detection of submarine cables and makes it very difficult to detect and locate them. Effective detection and accurate positioning of overlapping buried submarine cables are of great economic value and practical significance for laying, timely maintenance and replacement of submarine cables. The conditions of the seafloor in the coastal area are complex, and to avoid mooring damage or shark bites, submarine cables are usually buried under the seafloor and coated with armored steel wire layers, which provide a prerequisite for magnetic detection. For the magnetic detection of crossover and overlapping buried submarine cables, the methods such as upward continuation or matched filtering are usually used to separate and identify magnetic anomalies in deep and shallow parts, but the separation effect is not ideal and the accuracy is low. In this paper, the wavelet multiscale decomposition method and empirical mode decomposition method are used to separate the magnetic anomaly signals in the deep and shallow parts of the overlapping buried submarine cables. The simulation results show that the signal separation effect of the two methods is ideal and can be effectively applied to the magnetic detection of overlapping buried submarine cables.
{"title":"Research on Magnetic Anomaly Signal Separation Method of Crossover or Overlapping Buried Submarine Cables","authors":"Zhou Chunkai","doi":"10.1109/COA50123.2021.9519929","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9519929","url":null,"abstract":"Due to the rapid development of submarine cable engineering, there is not only crossover between submarine cables, but also overlapping of different types of buried submarine cables, which causes serious interference to the detection of submarine cables and makes it very difficult to detect and locate them. Effective detection and accurate positioning of overlapping buried submarine cables are of great economic value and practical significance for laying, timely maintenance and replacement of submarine cables. The conditions of the seafloor in the coastal area are complex, and to avoid mooring damage or shark bites, submarine cables are usually buried under the seafloor and coated with armored steel wire layers, which provide a prerequisite for magnetic detection. For the magnetic detection of crossover and overlapping buried submarine cables, the methods such as upward continuation or matched filtering are usually used to separate and identify magnetic anomalies in deep and shallow parts, but the separation effect is not ideal and the accuracy is low. In this paper, the wavelet multiscale decomposition method and empirical mode decomposition method are used to separate the magnetic anomaly signals in the deep and shallow parts of the overlapping buried submarine cables. The simulation results show that the signal separation effect of the two methods is ideal and can be effectively applied to the magnetic detection of overlapping buried submarine cables.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117176624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-14DOI: 10.1109/COA50123.2021.9520008
Zhu Lin, Zhou Yan, He Xinyi
In this work, combining the Reynolds Averaged Navier-Stokes(RANS) equation with the turbulence model RNG k-ε method is used to calculate the flow field of the model adopted simple geometries as submerged objects. The flow field characteristics of the model surface pressure, velocity distribution, vortex core region distribution features and evolution of vortex in the wake during the straight movement state are calculated. The calculation results are compared with the experimental results well. The vortex-wake continues to propagate in the direction behind the vehicle. Therefore, the vortex wake can transmit in the water for a long distance which represents an invaluable source of information for detection and tracking underwater.
{"title":"Numerical Simulation of Underwater Vehicle Wake Field","authors":"Zhu Lin, Zhou Yan, He Xinyi","doi":"10.1109/COA50123.2021.9520008","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9520008","url":null,"abstract":"In this work, combining the Reynolds Averaged Navier-Stokes(RANS) equation with the turbulence model RNG k-ε method is used to calculate the flow field of the model adopted simple geometries as submerged objects. The flow field characteristics of the model surface pressure, velocity distribution, vortex core region distribution features and evolution of vortex in the wake during the straight movement state are calculated. The calculation results are compared with the experimental results well. The vortex-wake continues to propagate in the direction behind the vehicle. Therefore, the vortex wake can transmit in the water for a long distance which represents an invaluable source of information for detection and tracking underwater.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129959608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the ocean front environment, the existence of ocean front has an important impact on sound propagation due to the obvious change of sound speed profile. According to the two-dimensional parameterized model of ocean temperature front constructed by Olivier et al, we build a two-dimensional parameterized feature model of ocean front based on sound speed profile, calculate and compare the influence of ocean front on convergence area by setting different ocean front environment. The results show that when the sound wave propagates from the warm water mass to the cold water mass, the convergence area moves forward, and the degree of the forward movement changes with the intensity of the ocean front; when the sound wave propagates from the cold water mass to the warm water mass, the convergence area moves backward, and the degree of the backward movement changes with the intensity of the ocean front. We also analyze the reasons for the formation of the acoustic shadow area at a specific location under the condition of strong ocean front when the sound wave propagates from the warm water mass to the cold water mass, which may provide a reference for the acoustic concealment of the target under the environment of ocean front.
{"title":"Ocean Front Model Based on Sound Speed Profile and its Influence on Sound Propagation","authors":"Yuyao Liu, Wen Chen, Wei Chen, Yu Chen, Lina Ma, Z. Meng","doi":"10.1109/COA50123.2021.9519871","DOIUrl":"https://doi.org/10.1109/COA50123.2021.9519871","url":null,"abstract":"In the ocean front environment, the existence of ocean front has an important impact on sound propagation due to the obvious change of sound speed profile. According to the two-dimensional parameterized model of ocean temperature front constructed by Olivier et al, we build a two-dimensional parameterized feature model of ocean front based on sound speed profile, calculate and compare the influence of ocean front on convergence area by setting different ocean front environment. The results show that when the sound wave propagates from the warm water mass to the cold water mass, the convergence area moves forward, and the degree of the forward movement changes with the intensity of the ocean front; when the sound wave propagates from the cold water mass to the warm water mass, the convergence area moves backward, and the degree of the backward movement changes with the intensity of the ocean front. We also analyze the reasons for the formation of the acoustic shadow area at a specific location under the condition of strong ocean front when the sound wave propagates from the warm water mass to the cold water mass, which may provide a reference for the acoustic concealment of the target under the environment of ocean front.","PeriodicalId":192644,"journal":{"name":"2021 OES China Ocean Acoustics (COA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128324016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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