Pub Date : 2024-06-03DOI: 10.1109/JOE.2024.3379484
Tianjiao Li;Bo Wang;Zhihong Deng;Mengyin Fu
Gravity gradient-aided inertial navigation is of great significance to the development of autonomous underwater vehicles (AUV). The matching algorithm is the core technology of gravity gradient-aided navigation. In this work, a weighted gravity gradient comprehensive image matching algorithm based on a genetic algorithm (GA) is proposed. This approach addresses the limitation of the comprehensive image matching algorithm in meeting real-time requirements. The characteristics of the gravity gradient reference map are analyzed, then the parallel feature matching methods of mathematical statistics, gray level concurrence matrix texture in the spatial domain and wavelet texture in the frequency domain are presented. In addition, the contribution rates of the independent components of the gravity gradient tensor are calculated, and dynamic weights are applied to synthesize the gravity gradient components. Finally, the longitude and latitude coordinates of the AUV to be estimated are integrated into a chromosome, and the fitness function is designed to realize the matching and positioning of the gravity gradient image based on the GA. The experimental results show that the positioning accuracy of the proposed algorithm in the straight trajectory segment and the entire U-shaped trajectory is 82.4% and 73.8% higher than that of the existing algorithms, respectively. It can be concluded that the proposed algorithm is real-time and has superior position correction performance for inertial navigation system.
重力梯度辅助惯性导航对自主潜水器（AUV）的发展具有重要意义。匹配算法是重力梯度辅助导航的核心技术。本研究提出了一种基于遗传算法（GA）的加权重力梯度综合图像匹配算法。这种方法解决了综合图像匹配算法在满足实时性要求方面的局限性。首先分析了重力梯度参考图的特征，然后介绍了数理统计、空间域灰度并发矩阵纹理和频域小波纹理的并行特征匹配方法。此外，还计算了重力梯度张量独立分量的贡献率，并应用动态权重合成重力梯度分量。最后，将待估算 AUV 的经纬度坐标整合到染色体中，并设计拟合函数，基于 GA 实现重力梯度图像的匹配和定位。实验结果表明，提出的算法在直线轨迹段和整个 U 形轨迹的定位精度分别比现有算法高 82.4% 和 73.8%。由此可以得出结论，所提出的算法具有实时性，在惯性导航系统中具有优越的位置校正性能。
{"title":"Genetic Algorithm-Based Weighted Comprehensive Image Matching Algorithm for Underwater Gravity Gradient-Aided Navigation","authors":"Tianjiao Li;Bo Wang;Zhihong Deng;Mengyin Fu","doi":"10.1109/JOE.2024.3379484","DOIUrl":"10.1109/JOE.2024.3379484","url":null,"abstract":"Gravity gradient-aided inertial navigation is of great significance to the development of autonomous underwater vehicles (AUV). The matching algorithm is the core technology of gravity gradient-aided navigation. In this work, a weighted gravity gradient comprehensive image matching algorithm based on a genetic algorithm (GA) is proposed. This approach addresses the limitation of the comprehensive image matching algorithm in meeting real-time requirements. The characteristics of the gravity gradient reference map are analyzed, then the parallel feature matching methods of mathematical statistics, gray level concurrence matrix texture in the spatial domain and wavelet texture in the frequency domain are presented. In addition, the contribution rates of the independent components of the gravity gradient tensor are calculated, and dynamic weights are applied to synthesize the gravity gradient components. Finally, the longitude and latitude coordinates of the AUV to be estimated are integrated into a chromosome, and the fitness function is designed to realize the matching and positioning of the gravity gradient image based on the GA. The experimental results show that the positioning accuracy of the proposed algorithm in the straight trajectory segment and the entire U-shaped trajectory is 82.4% and 73.8% higher than that of the existing algorithms, respectively. It can be concluded that the proposed algorithm is real-time and has superior position correction performance for inertial navigation system.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1647-1656"},"PeriodicalIF":3.8,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1109/JOE.2024.3374424
Kang-Hoon Choi;Jee Woong Choi;Sunhyo Kim;Peter H. Dahl;David R. Dall'Osto;Hee Chun Song
Underwater acoustic communication is heavily influenced by intersymbol interference caused by the delay spread of multipaths. In this article, communication sequences transmitted from a drifting source were received by a fixed acoustic vector receiver system consisting of an accelerometer-based vector sensor and a pressure sensor, which can measure the three-directional components of vector quantity and pressure at a point. The underwater acoustic communication experiment was conducted in water approximately 30 m deep off the south coast of Geoje Island, South Korea, in May 2017 during the Korea Reverberation Experiment. Acceleration signals received by the vector sensor were converted to pressure-equivalent particle velocities, which were then used as input for a four-channel communication system together with acoustic pressure. These four channels have multipaths with different amplitudes but the same delay times, providing directional diversity that differs from the spatial diversity provided by hydrophone arrays. To improve the communication performance obtained from directional diversity, the Multichannel Combined Bidirectional Block-based Time Reversal Technique was used, which combines bidirectional equalization with time-reversal diversity and block-based time reversal that was robust against time-varying channels. Communication performance was compared with the outcomes produced by several other time reversal techniques. The results show that the Multichannel Combined Bidirectional Block-based Time Reversal Technique using a vector sensor achieved superior performance under the environmental conditions considered in this article.
{"title":"Experimental Study on Performance Improvement of Underwater Acoustic Communication Using a Single Vector Sensor","authors":"Kang-Hoon Choi;Jee Woong Choi;Sunhyo Kim;Peter H. Dahl;David R. Dall'Osto;Hee Chun Song","doi":"10.1109/JOE.2024.3374424","DOIUrl":"10.1109/JOE.2024.3374424","url":null,"abstract":"Underwater acoustic communication is heavily influenced by intersymbol interference caused by the delay spread of multipaths. In this article, communication sequences transmitted from a drifting source were received by a fixed acoustic vector receiver system consisting of an accelerometer-based vector sensor and a pressure sensor, which can measure the three-directional components of vector quantity and pressure at a point. The underwater acoustic communication experiment was conducted in water approximately 30 m deep off the south coast of Geoje Island, South Korea, in May 2017 during the Korea Reverberation Experiment. Acceleration signals received by the vector sensor were converted to pressure-equivalent particle velocities, which were then used as input for a four-channel communication system together with acoustic pressure. These four channels have multipaths with different amplitudes but the same delay times, providing directional diversity that differs from the spatial diversity provided by hydrophone arrays. To improve the communication performance obtained from directional diversity, the Multichannel Combined Bidirectional Block-based Time Reversal Technique was used, which combines bidirectional equalization with time-reversal diversity and block-based time reversal that was robust against time-varying channels. Communication performance was compared with the outcomes produced by several other time reversal techniques. The results show that the Multichannel Combined Bidirectional Block-based Time Reversal Technique using a vector sensor achieved superior performance under the environmental conditions considered in this article.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1574-1587"},"PeriodicalIF":3.8,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10545562","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1109/JOE.2024.3374465
Ole Jacob Lorentzen;Torstein Olsmo Sæbø;Alan J. Hunter;Roy Edgar Hansen
Synthetic aperture sonar interferometry relies on the interferogram of two single look complex images to estimate bathymetry. The phase difference measurements have variance, which is typically reduced by spatial smoothing at the cost of horizontal resolution. The high resolution intensity image is related to the bathymetry because of the observation geometry. We therefore suggest an approach that constrains the filtering around edges found by intensity image segmentation. We demonstrate our suggested method on simulated data and show quantitative and qualitative improvements in both the horizontal resolution and the shape resolvability of small objects. We demonstrate a 30% improvement in RMSE of the bathymetric estimate, and observe that the estimated bathymetry more closely renders the real object shape for a small, but elevated object. We demonstrate our suggested method on real data and show similar results.
{"title":"Synthetic Aperture Sonar Interferogram Filtering by Intensity Image Segmentation","authors":"Ole Jacob Lorentzen;Torstein Olsmo Sæbø;Alan J. Hunter;Roy Edgar Hansen","doi":"10.1109/JOE.2024.3374465","DOIUrl":"10.1109/JOE.2024.3374465","url":null,"abstract":"Synthetic aperture sonar interferometry relies on the interferogram of two single look complex images to estimate bathymetry. The phase difference measurements have variance, which is typically reduced by spatial smoothing at the cost of horizontal resolution. The high resolution intensity image is related to the bathymetry because of the observation geometry. We therefore suggest an approach that constrains the filtering around edges found by intensity image segmentation. We demonstrate our suggested method on simulated data and show quantitative and qualitative improvements in both the horizontal resolution and the shape resolvability of small objects. We demonstrate a 30% improvement in RMSE of the bathymetric estimate, and observe that the estimated bathymetry more closely renders the real object shape for a small, but elevated object. We demonstrate our suggested method on real data and show similar results.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1516-1529"},"PeriodicalIF":3.8,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10545427","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141945757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1109/JOE.2024.3364788
Karl von Ellenrieder
This marks the 14th year where we celebrate excellence in review. We extend our deep appreciation to all the reviewers and Associate Editors who have generously contributed their time and expertise toward the editorial process of the journal.
{"title":"Excellence in Review 2023","authors":"Karl von Ellenrieder","doi":"10.1109/JOE.2024.3364788","DOIUrl":"https://doi.org/10.1109/JOE.2024.3364788","url":null,"abstract":"This marks the 14th year where we celebrate excellence in review. We extend our deep appreciation to all the reviewers and Associate Editors who have generously contributed their time and expertise toward the editorial process of the journal.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 2","pages":"329-331"},"PeriodicalIF":4.1,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10500510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1109/JOE.2024.3369707
Hai-Long Su;Peng-Lang Shui
Radar high-resolution range profiles (HRRPs) of ships are important in ship classification and recognition. Sparse recovery algorithms are a major tool for acquiring HRRPs from radar returns. Statistical models of ship HRRPs and sea clutter form the foundation to develop effective and efficient algorithms. In this article, ship HRRPs are modeled using biparametric lognormal distributions with heavy tails and high sparsity. Sea clutter is modeled using a compound-Gaussian model with inverse Gaussian texture (CGIG) distributions. Based on the two models, a fast sparse recovery algorithm, named the Amplitude–Position Bi-iterative Sparse Recovery Algorithm, is proposed to estimate ship HRRPs. In addition to sparsity along range cells, ship HRRPs exhibit nongrid structure, and ship scatterers are frequently not located at the centers of range cells, resulting in microposition offsets. The range-oversampled model can handle nongrid structures but requires excessive computational resources. In this context, a ship HRRP is represented by a complex amplitude vector and a real position vector. The bi-iterative algorithm is designed to alternatively optimize the two vectors. When the latter is held constant, the former is optimized using the sparse recovery through iterative minimization algorithm based on the lognormal ship HRRP model and the CGIG sea clutter model. When the former is held constant, the latter is optimized using the quasi-Newton algorithm. Simulation and measured data are employed to examine the proposed bi-iterative algorithm. The experiments demonstrate that it provides better estimates of ship HRRPs in shorter CPU time compared to the existing algorithms.
{"title":"Fast Estimation of Complex High-Resolution Range Profiles of Ships via Amplitude–Position Bi-Iterative Sparse Recovery Algorithm","authors":"Hai-Long Su;Peng-Lang Shui","doi":"10.1109/JOE.2024.3369707","DOIUrl":"10.1109/JOE.2024.3369707","url":null,"abstract":"Radar high-resolution range profiles (HRRPs) of ships are important in ship classification and recognition. Sparse recovery algorithms are a major tool for acquiring HRRPs from radar returns. Statistical models of ship HRRPs and sea clutter form the foundation to develop effective and efficient algorithms. In this article, ship HRRPs are modeled using biparametric lognormal distributions with heavy tails and high sparsity. Sea clutter is modeled using a compound-Gaussian model with inverse Gaussian texture (CGIG) distributions. Based on the two models, a fast sparse recovery algorithm, named the Amplitude–Position Bi-iterative Sparse Recovery Algorithm, is proposed to estimate ship HRRPs. In addition to sparsity along range cells, ship HRRPs exhibit nongrid structure, and ship scatterers are frequently not located at the centers of range cells, resulting in microposition offsets. The range-oversampled model can handle nongrid structures but requires excessive computational resources. In this context, a ship HRRP is represented by a complex amplitude vector and a real position vector. The bi-iterative algorithm is designed to alternatively optimize the two vectors. When the latter is held constant, the former is optimized using the sparse recovery through iterative minimization algorithm based on the lognormal ship HRRP model and the CGIG sea clutter model. When the former is held constant, the latter is optimized using the quasi-Newton algorithm. Simulation and measured data are employed to examine the proposed bi-iterative algorithm. The experiments demonstrate that it provides better estimates of ship HRRPs in shorter CPU time compared to the existing algorithms.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"870-882"},"PeriodicalIF":3.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1109/JOE.2024.3352714
Zachary L. Cooper-Baldock;Paulo E. Santos;Russell S. A. Brinkworth;Karl Sammut
The development of extra-large uncrewed underwater vehicles (XLUUVs) presents an opportunity for transporting smaller uncrewed or autonomous underwater vehicles (UUV/AUVs) over long distances, within an XLUUV's payload bay, enabling energy-constrained AUVs to spend longer periods on station rather than in transit to-and-from their operational areas. Existing launch and recovery techniques for AUV platforms have focused on the use of static docks, towed docks, and surface vehicle dock recovery. This article seeks to determine the optimal approach configuration and feasibility of recovering an AUV, via an XLUUV's payload bay, while underway. Optimality was assessed via an analysis of drag, pressure, turbulence, and flow-field phenomena exerted on the AUV undertaking berthing. To make these determinations, a converged and validated computational fluid dynamics simulation was performed using ANSYS Fluent. The simulation assessed two variations to the AUV's approach: path-aligned and flow-aligned, with respect to the AUV's bow. These simulations were repeated across three different speeds and trajectories. The most optimal approach was identified to be the 1 knot, flow-aligned, high steepness trajectory. This approach correlated with reduced propulsion induced effects, more consistent lift and drag effects, and reduced turbulence intensity, kinetic energy, and vortical effects when compared with the other approaches under analysis.
{"title":"Hydrodynamic Analysis of Payload Bay Berthing for Underwater Vehicles","authors":"Zachary L. Cooper-Baldock;Paulo E. Santos;Russell S. A. Brinkworth;Karl Sammut","doi":"10.1109/JOE.2024.3352714","DOIUrl":"10.1109/JOE.2024.3352714","url":null,"abstract":"The development of extra-large uncrewed underwater vehicles (XLUUVs) presents an opportunity for transporting smaller uncrewed or autonomous underwater vehicles (UUV/AUVs) over long distances, within an XLUUV's payload bay, enabling energy-constrained AUVs to spend longer periods on station rather than in transit to-and-from their operational areas. Existing launch and recovery techniques for AUV platforms have focused on the use of static docks, towed docks, and surface vehicle dock recovery. This article seeks to determine the optimal approach configuration and feasibility of recovering an AUV, via an XLUUV's payload bay, while underway. Optimality was assessed via an analysis of drag, pressure, turbulence, and flow-field phenomena exerted on the AUV undertaking berthing. To make these determinations, a converged and validated computational fluid dynamics simulation was performed using ANSYS Fluent. The simulation assessed two variations to the AUV's approach: path-aligned and flow-aligned, with respect to the AUV's bow. These simulations were repeated across three different speeds and trajectories. The most optimal approach was identified to be the 1 knot, flow-aligned, high steepness trajectory. This approach correlated with reduced propulsion induced effects, more consistent lift and drag effects, and reduced turbulence intensity, kinetic energy, and vortical effects when compared with the other approaches under analysis.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"727-748"},"PeriodicalIF":3.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-10DOI: 10.1109/JOE.2024.3364670
Yushan Sun;Haotian Zheng;Guocheng Zhang;Jingfei Ren;Guoyang Shu
In the realm of oceanic exploration, sidescan sonar's significance is indisputable. However, the inherent challenges of low resolution and robust noise interference in sidescan sonar images have presented a formidable barrier to semantic segmentation in target regions. To address this, we propose a novel CGF-Unet framework, amalgamating Unet with global features, for precise and rapid sidescan sonar image segmentation. Leveraging both Transformers and Unet, CGF-Unet strategically introduces Transformer Blocks during downsampling and upsampling, amplifying access to comprehensive global insights and synergizing Transformer's potent sequence encoding with convolutional neural network's (CNN) holistic perception and spatial invariance. The incorporation of Conv-Attention within the Transformer Block streamlines model training parameters, accelerates training pace, and bolsters learning prowess. By implementing a weighted loss function, we navigate the challenge posed by skewed positive and negative samples, thereby elevating segmentation accuracy. Demonstrating its novelty, on distinct sidescan sonar data sets, we achieve exceptional mIOU scores of 89.3% and 86.5%, surpassing existing methodologies in precision. Remarkably, even amidst noise perturbation, the method maintains robust performance.
{"title":"CGF-Unet: Semantic Segmentation of Sidescan Sonar Based on Unet Combined With Global Features","authors":"Yushan Sun;Haotian Zheng;Guocheng Zhang;Jingfei Ren;Guoyang Shu","doi":"10.1109/JOE.2024.3364670","DOIUrl":"10.1109/JOE.2024.3364670","url":null,"abstract":"In the realm of oceanic exploration, sidescan sonar's significance is indisputable. However, the inherent challenges of low resolution and robust noise interference in sidescan sonar images have presented a formidable barrier to semantic segmentation in target regions. To address this, we propose a novel CGF-Unet framework, amalgamating Unet with global features, for precise and rapid sidescan sonar image segmentation. Leveraging both Transformers and Unet, CGF-Unet strategically introduces Transformer Blocks during downsampling and upsampling, amplifying access to comprehensive global insights and synergizing Transformer's potent sequence encoding with convolutional neural network's (CNN) holistic perception and spatial invariance. The incorporation of Conv-Attention within the Transformer Block streamlines model training parameters, accelerates training pace, and bolsters learning prowess. By implementing a weighted loss function, we navigate the challenge posed by skewed positive and negative samples, thereby elevating segmentation accuracy. Demonstrating its novelty, on distinct sidescan sonar data sets, we achieve exceptional mIOU scores of 89.3% and 86.5%, surpassing existing methodologies in precision. Remarkably, even amidst noise perturbation, the method maintains robust performance.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"963-975"},"PeriodicalIF":3.8,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-10DOI: 10.1109/JOE.2024.3365169
Alfie Anthony Treloar;Hugh Maclean;Jan Bujalka;Jon Narramore;Ben Thomas;Philippe Blondel;Alan Hunter
This article presents the first demonstration of beamforming, detection, and bearing estimation of an underwater acoustic source from an eight-element thin line hydrophone array towed behind the AutoNaut wave-propelled uncrewed surface vessel. This has been achieved in situ and in real time during an experimental sea trial off the coast of Plymouth, U.K. A controlled acoustic source was towed from a support vessel while emitting seven tonals with frequencies between 480–1630 Hz and source levels between 93–126 dB. This allowed the detection performance of the array to be assessed and demonstrated for an acoustic source with known bearing and range. In postprocessing, the shape of the array was estimated using a cubic spline model, exploiting measurements from pressure and three-axis compass sensors integrated at each end of the array. The beamforming was repeated using the estimated array shape to infer the hydrophone positions, which resulted in a median improvement of 0.38 dB and maximum of 5.8 dB in the MUSIC beamforming output, and a potential reduction in the left/right bearing estimation ambiguities. The outcomes of this work demonstrate that the AutoNaut is an effective platform for towed array passive acoustic monitoring.
本文首次展示了在 AutoNaut 波浪推进式无人驾驶水面舰艇后面拖曳的八元细线水听器阵列对水下声源的波束成形、探测和方位估计。这是在英国普利茅斯海岸外的一次实验性海试中就地实时实现的。一个受控声源由一艘支持船拖曳，同时发出频率在 480-1630 Hz 之间、声源电平在 93-126 dB 之间的七种音调。这样就可以对已知方位和范围的声源进行阵列探测性能评估和演示。在后处理过程中，利用集成在阵列两端的压力和三轴罗盘传感器的测量结果，使用三次样条模型对阵列的形状进行了估计。使用估计的阵列形状重复进行波束成形，以推断水听器的位置，从而使 MUSIC 波束成形输出的中值提高了 0.38 dB，最大值提高了 5.8 dB，并有可能减少左/右方位估计的模糊性。这项工作的成果表明，AutoNaut 是拖曳阵列被动声学监测的有效平台。
{"title":"Real-Time In-Situ Passive Acoustic Array Beamforming From the AutoNaut Wave-Propelled Uncrewed Surface Vessel","authors":"Alfie Anthony Treloar;Hugh Maclean;Jan Bujalka;Jon Narramore;Ben Thomas;Philippe Blondel;Alan Hunter","doi":"10.1109/JOE.2024.3365169","DOIUrl":"10.1109/JOE.2024.3365169","url":null,"abstract":"This article presents the first demonstration of beamforming, detection, and bearing estimation of an underwater acoustic source from an eight-element thin line hydrophone array towed behind the AutoNaut wave-propelled uncrewed surface vessel. This has been achieved in situ and in real time during an experimental sea trial off the coast of Plymouth, U.K. A controlled acoustic source was towed from a support vessel while emitting seven tonals with frequencies between 480–1630 Hz and source levels between 93–126 dB. This allowed the detection performance of the array to be assessed and demonstrated for an acoustic source with known bearing and range. In postprocessing, the shape of the array was estimated using a cubic spline model, exploiting measurements from pressure and three-axis compass sensors integrated at each end of the array. The beamforming was repeated using the estimated array shape to infer the hydrophone positions, which resulted in a median improvement of 0.38 dB and maximum of 5.8 dB in the MUSIC beamforming output, and a potential reduction in the left/right bearing estimation ambiguities. The outcomes of this work demonstrate that the AutoNaut is an effective platform for towed array passive acoustic monitoring.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"713-726"},"PeriodicalIF":3.8,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cyclostationary features of communication signals are known to compromise the security of transmissions against eavesdropping attacks. They can be used for signal detection, modulation recognition, or for the blind estimation of physical layer parameters. This work presents a method that voluntarily distorts the transmitted signal to hide the cyclostationary patterns. This distortion is obtained with a pseudorandom time-varying filter that combines time warping and dispersive filtering. The proposed method acts as a plug-in that is applicable to most of the existing transmission schemes. It is shown that this distortion can be easily reversed by the cooperative receiver using a simple matched filter combined with resampling. In the context of underwater acoustic communications, numerical results with replay simulations of channels measured at sea illustrate the benefits of the proposed method. For both a coherent and a noncoherent modem, the induced distortion is shown to be robust to existing cyclostationary attacks, at the cost of a slight reduction in data rate. Furthermore, no performance degradation in terms of packet error ratio is observed for cooperative transmissions.
{"title":"Cyclostationary Feature Distortion for Secure Underwater Acoustic Transmissions","authors":"François-Xavier Socheleau;Christophe Laot;Sébastien Houcke","doi":"10.1109/JOE.2024.3366283","DOIUrl":"10.1109/JOE.2024.3366283","url":null,"abstract":"Cyclostationary features of communication signals are known to compromise the security of transmissions against eavesdropping attacks. They can be used for signal detection, modulation recognition, or for the blind estimation of physical layer parameters. This work presents a method that voluntarily distorts the transmitted signal to hide the cyclostationary patterns. This distortion is obtained with a pseudorandom time-varying filter that combines time warping and dispersive filtering. The proposed method acts as a plug-in that is applicable to most of the existing transmission schemes. It is shown that this distortion can be easily reversed by the cooperative receiver using a simple matched filter combined with resampling. In the context of underwater acoustic communications, numerical results with replay simulations of channels measured at sea illustrate the benefits of the proposed method. For both a coherent and a noncoherent modem, the induced distortion is shown to be robust to existing cyclostationary attacks, at the cost of a slight reduction in data rate. Furthermore, no performance degradation in terms of packet error ratio is observed for cooperative transmissions.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"1051-1066"},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-09DOI: 10.1109/JOE.2024.3360515
Jessica E. Carilli;Regina A. Guazzo;Angelica R. Rodriguez
Determining accurate latitude and longitude positions in GPS-denied environments is a long-standing issue in the fields of navigation and positioning. Much of the ongoing research in these fields centers on costly, evermore sophisticated sensor and algorithm development. Yet, several applications exist, which do not require high levels of precision or investment. This article describes a simple and cost-effective solution developed to map generalized, georeferenced bathymetry underneath piers using an uncrewed surface vessel (USV) with the minimum number of instruments. Under-pier areas are challenging environments constrained by tides, ship movements, varying pier architectures, and sporadic or nonexistent GPS signals. Working within these constraints, we used a small, remotely operated USV with an integrated single-beam sonar system (for depth, z measurements) and geographic positioning system (GPS; for some latitude/longitude, x,y positions) and also used an ultrashort baseline (USBL) acoustic positioning system to determine x,y positions when GPS was denied under the pier. We developed data processing steps to correct the positional and bathymetric estimates and assessed the accuracy of these values. We found that our quality-controlled USBL positions were reasonably precise compared with GPS positions (1.2 and 0.6 m average standard deviation, respectively), although there was also an apparent horizontal offset between USBL and GPS positions that averaged about 3.25 m. However, comparing the sediment volume under piers estimated using this low-cost USV method with that calculated from sidescan sonar-generated bathymetric maps, we found that these volume estimates agreed closely, within $sim$ 0.6%. This manuscript presents the methods developed, including the approach used to integrate these different data streams, to allow other researchers to collect and process similar data sets in constrained environments.
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