Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050669
Li Hua, Zhang Xiaojun
With the development of marine economy and data positioning technology, A large amount of vessel trajectory data has been generated. Data compression has become the key issue in the research of vessel trajectory big data. Since the compression rate of the existing vessel trajectory compression algorithms was not adjustable, we proposed a vessel trajectory compression algorithm with adjustable compression rate based on Sliding-Windows(SW) algorithm. The main idea was to adjust the compression rate by dynamically updating the vertical Euclidean distance threshold. The proposed algorithm could adapt to the dynamic change of channel capacity by dynamically adjusting the compression rate in online compression. The simulation results showed that compared with the traditional SW algorithm, the proposed algorithm not only realized the dynamic adjustment of compression rate, but also the compression error was less than that of the SW algorithm. Meanwhile the increase of computational complexity was almost negligible. This algorithm could also be used for online compression of other kinds of trajectory data.
{"title":"Compatible Sliding-Windows Algorithm for Vessel Trajectory Compression","authors":"Li Hua, Zhang Xiaojun","doi":"10.1109/ICICSP55539.2022.10050669","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050669","url":null,"abstract":"With the development of marine economy and data positioning technology, A large amount of vessel trajectory data has been generated. Data compression has become the key issue in the research of vessel trajectory big data. Since the compression rate of the existing vessel trajectory compression algorithms was not adjustable, we proposed a vessel trajectory compression algorithm with adjustable compression rate based on Sliding-Windows(SW) algorithm. The main idea was to adjust the compression rate by dynamically updating the vertical Euclidean distance threshold. The proposed algorithm could adapt to the dynamic change of channel capacity by dynamically adjusting the compression rate in online compression. The simulation results showed that compared with the traditional SW algorithm, the proposed algorithm not only realized the dynamic adjustment of compression rate, but also the compression error was less than that of the SW algorithm. Meanwhile the increase of computational complexity was almost negligible. This algorithm could also be used for online compression of other kinds of trajectory data.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116049951","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050656
Zhixia Wu, Shengqi Zhu, Jingwei Xu, Lan Lan, Mengdi Zhang, Ximin Li
In the issue of interference suppression, the performance of traditional adaptive methods will decrease when mainlobe interference and sidelobe interference have angle error. To this end, a robust adaptive beamforming technique based on frequency diversity array (FDA) multiple-input multiple-output (MIMO) is proposed in this work. Firstly, preprocessing in data domain is adopted for mainlobe interference cancellation. Then, the sidelobe interference is suppressed in the receiving dimension. Finally, robust adaptive beamforming method is applied to suppress sidelobe interference. Simulation results show the effectiveness of the proposed algorithm.
{"title":"A Robust Interference Suppression Method Based on FDA-MIMO Radar","authors":"Zhixia Wu, Shengqi Zhu, Jingwei Xu, Lan Lan, Mengdi Zhang, Ximin Li","doi":"10.1109/ICICSP55539.2022.10050656","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050656","url":null,"abstract":"In the issue of interference suppression, the performance of traditional adaptive methods will decrease when mainlobe interference and sidelobe interference have angle error. To this end, a robust adaptive beamforming technique based on frequency diversity array (FDA) multiple-input multiple-output (MIMO) is proposed in this work. Firstly, preprocessing in data domain is adopted for mainlobe interference cancellation. Then, the sidelobe interference is suppressed in the receiving dimension. Finally, robust adaptive beamforming method is applied to suppress sidelobe interference. Simulation results show the effectiveness of the proposed algorithm.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122796236","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050665
Cheng Ken, Wang Fangyong, Du Shuanping
Non-cooperative passive detection is a new type of underwater acoustic detection technology, which originated in the field of radar. It detects the target scattered echoes through active signals emitted by non-cooperative sources. Since this mode can perform high-gain detection of long-distance targets without transmitting a detection signal, it has great development prospects. In this paper, a target detection method based on non-cooperative pulse signal is proposed, and the non-cooperative transmitted signal is reconstructed by fractional Fourier transform (FRFT) as a matched filter template. Taking the emission sound source as the positioning assistant point, the position of the assistant point is determined by using the dual-array positioning technology, and the target is measured by calculating the relative positional relationship between the assistant point and the target. The simulation experiments show that the non-cooperative target positioning technology used in this paper has obvious advantages compared with the traditional dual-array passive positioning technology. The mean positioning error of this method for passive targets at a distance of 15km is less than 5%.
{"title":"Passive Detection Method Based on Non-cooperative Underwater Acoustic Pulse Signal","authors":"Cheng Ken, Wang Fangyong, Du Shuanping","doi":"10.1109/ICICSP55539.2022.10050665","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050665","url":null,"abstract":"Non-cooperative passive detection is a new type of underwater acoustic detection technology, which originated in the field of radar. It detects the target scattered echoes through active signals emitted by non-cooperative sources. Since this mode can perform high-gain detection of long-distance targets without transmitting a detection signal, it has great development prospects. In this paper, a target detection method based on non-cooperative pulse signal is proposed, and the non-cooperative transmitted signal is reconstructed by fractional Fourier transform (FRFT) as a matched filter template. Taking the emission sound source as the positioning assistant point, the position of the assistant point is determined by using the dual-array positioning technology, and the target is measured by calculating the relative positional relationship between the assistant point and the target. The simulation experiments show that the non-cooperative target positioning technology used in this paper has obvious advantages compared with the traditional dual-array passive positioning technology. The mean positioning error of this method for passive targets at a distance of 15km is less than 5%.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122883224","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050582
Jun-qing Ye, Yi-Hao Peng, Peichang Zhang, Qiang Li, Lei Huang
Reconfigurable Intelligent surface (RIS) has been envisioned as a promising technique for the 6th generation (6G) communications. Generally, a RIS is consist of a number of reflective elements that collaboratively adjust the direction of incident signals, and is considered to have the advantages of combating fading and shadowing problems in communication systems. In this article, by exploiting these RIS advantages, we propose to utilize the concept of RIS for the non-line-of-sight (NLOS) target radar detection. More specifically, we opt for using semi-definite relaxing (SDR) to obtain the optimal phase shift of RIS for each detection angle to build a code-book for all the optimal phase shifts, which can then be used for detecting the direction of target. The Doppler frequency shift can also be obtained via processing the echo with maximum power. Simulation results show that RIS is capable of significantly improving the coverage of radar detection.
{"title":"RIS-Assisted Radar NLOS Target Detection","authors":"Jun-qing Ye, Yi-Hao Peng, Peichang Zhang, Qiang Li, Lei Huang","doi":"10.1109/ICICSP55539.2022.10050582","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050582","url":null,"abstract":"Reconfigurable Intelligent surface (RIS) has been envisioned as a promising technique for the 6th generation (6G) communications. Generally, a RIS is consist of a number of reflective elements that collaboratively adjust the direction of incident signals, and is considered to have the advantages of combating fading and shadowing problems in communication systems. In this article, by exploiting these RIS advantages, we propose to utilize the concept of RIS for the non-line-of-sight (NLOS) target radar detection. More specifically, we opt for using semi-definite relaxing (SDR) to obtain the optimal phase shift of RIS for each detection angle to build a code-book for all the optimal phase shifts, which can then be used for detecting the direction of target. The Doppler frequency shift can also be obtained via processing the echo with maximum power. Simulation results show that RIS is capable of significantly improving the coverage of radar detection.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122944245","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050652
Xingguo Chen, Lin Geng, Geoffrey J. Zhang
A sparse real-time near-field acoustic holography method is proposed to precisely and stably reconstruct a transient sound field. In the proposed method, by using a time-domain impulse response function, a time domain convolution equation between the time-wavenumber pressure spectra on the hologram and reconstruction planes is first established. Then, for obtaining the time-wavenumber pressure spectrum on the reconstruction plane, a smoothed $ell_{0}$ -norm optimization algorithm is applied to solve the serious ill-conditioned problem in the inverse process. The key of solving this problem is to approximate replace the discontinuous $ell_{0}$ -norm by using a suitable continuous Gaussian function family, and the steepest ascent algorithm is introduced to minimize the continuous function for obtaining the optimal solution. Finally, the pressure time-wavenumber spectra on the reconstruction plane at all wavenumbers for all times are solved, and the corresponding time-dependent pressures are acquired by the two-dimensional inverse Fourier transform. A numerical simulation with a baffled planar piston is conducted to observe the performance of the proposed method. The simulation results prove that the proposed method can accurately reconstruct the transient sound field. The reconstruction results are also compared to those of real-time near-field acoustic holography with Tikhonov regularization and YALL1 modal to verify the superiority of the proposed method.
{"title":"A Sparse Real Time Acoustic Holography Method for Nonstationary Acoustic Source Reconstruction","authors":"Xingguo Chen, Lin Geng, Geoffrey J. Zhang","doi":"10.1109/ICICSP55539.2022.10050652","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050652","url":null,"abstract":"A sparse real-time near-field acoustic holography method is proposed to precisely and stably reconstruct a transient sound field. In the proposed method, by using a time-domain impulse response function, a time domain convolution equation between the time-wavenumber pressure spectra on the hologram and reconstruction planes is first established. Then, for obtaining the time-wavenumber pressure spectrum on the reconstruction plane, a smoothed $ell_{0}$ -norm optimization algorithm is applied to solve the serious ill-conditioned problem in the inverse process. The key of solving this problem is to approximate replace the discontinuous $ell_{0}$ -norm by using a suitable continuous Gaussian function family, and the steepest ascent algorithm is introduced to minimize the continuous function for obtaining the optimal solution. Finally, the pressure time-wavenumber spectra on the reconstruction plane at all wavenumbers for all times are solved, and the corresponding time-dependent pressures are acquired by the two-dimensional inverse Fourier transform. A numerical simulation with a baffled planar piston is conducted to observe the performance of the proposed method. The simulation results prove that the proposed method can accurately reconstruct the transient sound field. The reconstruction results are also compared to those of real-time near-field acoustic holography with Tikhonov regularization and YALL1 modal to verify the superiority of the proposed method.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124884517","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050620
Yuanyuan Wang, Haosheng Fu, Fengzhou Dai
High-resolution imaging from gapped data has become a research hotspot in radar imaging field. Among many imaging algorithms, sparse Bayesian learning (SBL) is more robust and has greater estimation accuracy, which attracts active interest from researchers. Unfortunately, the inversion and multiplying operations are involved in each iteration of SBL lead to heavy computational complexity when they are implemented directly. In this paper, we propose a fast Fourier dictionary (FD)-based SBL algorithm to solve high-resolution imaging from gapped data, greatly reducing the calculation cost. Finally, the experimental results verify the effectiveness of the proposed method.
{"title":"High-Resolution Imaging from Gapped Data Based on Fast Sparse Bayesian Learning","authors":"Yuanyuan Wang, Haosheng Fu, Fengzhou Dai","doi":"10.1109/ICICSP55539.2022.10050620","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050620","url":null,"abstract":"High-resolution imaging from gapped data has become a research hotspot in radar imaging field. Among many imaging algorithms, sparse Bayesian learning (SBL) is more robust and has greater estimation accuracy, which attracts active interest from researchers. Unfortunately, the inversion and multiplying operations are involved in each iteration of SBL lead to heavy computational complexity when they are implemented directly. In this paper, we propose a fast Fourier dictionary (FD)-based SBL algorithm to solve high-resolution imaging from gapped data, greatly reducing the calculation cost. Finally, the experimental results verify the effectiveness of the proposed method.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125077154","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050571
Xu Jin, Zhu Wei, Ding Shengyao, Hu Kunjiao
The multi-path signal and the direct signal, lying within a beam-width of the receiving antenna, are highly correlated, which cause badly effect to the performance of low-angle altitude measurement for very high frequency (VHF) radar. A novel adaptive altitude measurement is proposed. Combine digital elevation model (DEM) with distributed sources model, a multipath signal model was constructed which is much closer to the practical rough reflection surface. The height of target was obtained through multi-dimension alternating projection and synthesized vector maximum likelihood algorithm. Simulation results and the measured data processing demonstrate the validity and feasibility of the proposed method.
{"title":"Adaptive Altitude Measurement Based on Digital Elevation Model in VHF Array Radar","authors":"Xu Jin, Zhu Wei, Ding Shengyao, Hu Kunjiao","doi":"10.1109/ICICSP55539.2022.10050571","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050571","url":null,"abstract":"The multi-path signal and the direct signal, lying within a beam-width of the receiving antenna, are highly correlated, which cause badly effect to the performance of low-angle altitude measurement for very high frequency (VHF) radar. A novel adaptive altitude measurement is proposed. Combine digital elevation model (DEM) with distributed sources model, a multipath signal model was constructed which is much closer to the practical rough reflection surface. The height of target was obtained through multi-dimension alternating projection and synthesized vector maximum likelihood algorithm. Simulation results and the measured data processing demonstrate the validity and feasibility of the proposed method.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121986634","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050627
Qixi Tan, W. Xie, Haojin Tang, Yanshan Li
Remote sensing images (RSI) have a large range of variations in the aspect of inter- and intra-class size variability across objects. As a key technology in the field of RSI processing, RSI object detection has been widely applied. Multilevel features fusion network is commonly used to improve the performance of object detection. However, the existing multilevel feature fusion networks for RSI lack the ability to combine global information. Aiming at this problem, A multi-scale attention adaptive network (MA2Net) is proposed to object detection in RSI. The main contributions of this paper are twofold. Firstly, a multi-scale attention adaptive network is designed to adaptively integrate the multilevel features. This network is composed of integrating (IG) block, channel self-attention (CS) block, and adaptive fusion (AF) block. Specifically, IG is designed to transform the multi-level features into an intermediate size. The CS block is an embedded gaussian self-attention module used to model the relationship between the feature channels. AF is developed to learn the multilevel expression of self-attention features to obtain multi-scale feature maps. Secondly, to achieve a balance between multi-task and higher accuracy, a feature align head is utilized to correctly locate and classify objects. The experimental results on DIOR show that our network can achieve higher detection accuracy than the state-of-the-art RSI object detector.
{"title":"Multi-scale Attention Adaptive Network for Object Detection in Remote Sensing Images","authors":"Qixi Tan, W. Xie, Haojin Tang, Yanshan Li","doi":"10.1109/ICICSP55539.2022.10050627","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050627","url":null,"abstract":"Remote sensing images (RSI) have a large range of variations in the aspect of inter- and intra-class size variability across objects. As a key technology in the field of RSI processing, RSI object detection has been widely applied. Multilevel features fusion network is commonly used to improve the performance of object detection. However, the existing multilevel feature fusion networks for RSI lack the ability to combine global information. Aiming at this problem, A multi-scale attention adaptive network (MA2Net) is proposed to object detection in RSI. The main contributions of this paper are twofold. Firstly, a multi-scale attention adaptive network is designed to adaptively integrate the multilevel features. This network is composed of integrating (IG) block, channel self-attention (CS) block, and adaptive fusion (AF) block. Specifically, IG is designed to transform the multi-level features into an intermediate size. The CS block is an embedded gaussian self-attention module used to model the relationship between the feature channels. AF is developed to learn the multilevel expression of self-attention features to obtain multi-scale feature maps. Secondly, to achieve a balance between multi-task and higher accuracy, a feature align head is utilized to correctly locate and classify objects. The experimental results on DIOR show that our network can achieve higher detection accuracy than the state-of-the-art RSI object detector.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124037913","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050622
Chen Ling, Li Qiang, Zhang Zhen
Civil aircraft noise is the main source of the airport and its surrounding areas, in recent years, with the continuous development of the air transport industry, aircraft noise is more and more concerned by the public, according to the International Civil Aviation Convention Annex 16 Volume I and China Civil Aviation Regulations CCAR36 Aircraft Type and Airworthiness Certification Noise Regulations. The noise limit requirements for transport aircraft are put forward. According to the requirements of the regulations, it is the key to determine that the aircraft meets the requirements of the regulations to obtain the noise data through flight test and to obtain the equivalent perceived noise level through data processing. In this paper, the noise data processing process and the key points are analyzed.
{"title":"Data Processing of Noise Flight Test for Large Civil Aircraft Type Certification","authors":"Chen Ling, Li Qiang, Zhang Zhen","doi":"10.1109/ICICSP55539.2022.10050622","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050622","url":null,"abstract":"Civil aircraft noise is the main source of the airport and its surrounding areas, in recent years, with the continuous development of the air transport industry, aircraft noise is more and more concerned by the public, according to the International Civil Aviation Convention Annex 16 Volume I and China Civil Aviation Regulations CCAR36 Aircraft Type and Airworthiness Certification Noise Regulations. The noise limit requirements for transport aircraft are put forward. According to the requirements of the regulations, it is the key to determine that the aircraft meets the requirements of the regulations to obtain the noise data through flight test and to obtain the equivalent perceived noise level through data processing. In this paper, the noise data processing process and the key points are analyzed.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128988107","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 : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050616
Mei Sun
The propagation properties of the vector sound field with a shallow receiver in the bottom-reflected zone of a shallow source in deep water are studied in this paper. Firstly, the properties of the sound rays arriving at the receiver position are studied. Secondly, theoretical analysis of the propagation property of the vector sound field is conducted by using the ray model. Thirdly, transmission losses of the sound pressure, the horizontal particle velocity and the vertical particle velocity are calculated by the RAM-PE model. The theoretical analysis and the simulation results show that the energy and the transmission losses of the horizontal particle velocity and the vertical particle velocity are closely related with the grazing angles of the eigenrays. The transmission loss difference between the vertical particle velocity and the horizontal particle velocity increases with the increase of the range from the source to the receiver, and satisfies Eq. (19) in this paper.
{"title":"Propagation of the Vector Sound Field in the Bottom-Reflected Zone in Deep Water","authors":"Mei Sun","doi":"10.1109/ICICSP55539.2022.10050616","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050616","url":null,"abstract":"The propagation properties of the vector sound field with a shallow receiver in the bottom-reflected zone of a shallow source in deep water are studied in this paper. Firstly, the properties of the sound rays arriving at the receiver position are studied. Secondly, theoretical analysis of the propagation property of the vector sound field is conducted by using the ray model. Thirdly, transmission losses of the sound pressure, the horizontal particle velocity and the vertical particle velocity are calculated by the RAM-PE model. The theoretical analysis and the simulation results show that the energy and the transmission losses of the horizontal particle velocity and the vertical particle velocity are closely related with the grazing angles of the eigenrays. The transmission loss difference between the vertical particle velocity and the horizontal particle velocity increases with the increase of the range from the source to the receiver, and satisfies Eq. (19) in this paper.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132500847","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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