Pub Date : 2024-11-14DOI: 10.1109/JOE.2024.3455560
Amit Agarwal;Ioannis Krikidis
This article investigates a simultaneous lightwave information and power transfer (SLIPT)-enabled two-user nonorthogonal multiple access setup for underwater wireless optical communication. We consider a turbulence-induced fading channel and apply successive interference cancellation at the near user. Specifically, an explicit expression for the power amplifier gain at the transmitter in terms of bias and power allocation coefficients (PACs) is derived to ensure linear operation of the light source (LS). Furthermore, to choose the bias and PACs values, we formulate an optimization problem to maximize fairness in data rate, while meeting a minimum harvested energy threshold controlled by a system defined factor $alpha in (0,1]$. Results indicate constant average data rates and harvested energy until a certain value of $alpha$, named the cut-in value. We also show that the cut-in value depends on the LS's maximum allowed bias current. Finally, we discuss how the proposed framework can be extended to more than two users. It is also shown that significant battery life improvement can be achieved by employing the SLIPT method. Specifically, for a four user scenario the nearest user positioned at 5 m from the source gets a battery life improvement of 38.5% when the data rate is approximately 1.75 b/s/Hz and an improvement of 62% when the data rate is 1 b/s/Hz.
{"title":"Fairness-Driven Optimization for NOMA-UWOC Systems With Energy Harvesting Requirements","authors":"Amit Agarwal;Ioannis Krikidis","doi":"10.1109/JOE.2024.3455560","DOIUrl":"https://doi.org/10.1109/JOE.2024.3455560","url":null,"abstract":"This article investigates a simultaneous lightwave information and power transfer (SLIPT)-enabled two-user nonorthogonal multiple access setup for underwater wireless optical communication. We consider a turbulence-induced fading channel and apply successive interference cancellation at the near user. Specifically, an explicit expression for the power amplifier gain at the transmitter in terms of bias and power allocation coefficients (PACs) is derived to ensure linear operation of the light source (LS). Furthermore, to choose the bias and PACs values, we formulate an optimization problem to maximize fairness in data rate, while meeting a minimum harvested energy threshold controlled by a system defined factor <inline-formula><tex-math>$alpha in (0,1]$</tex-math></inline-formula>. Results indicate constant average data rates and harvested energy until a certain value of <inline-formula><tex-math>$alpha$</tex-math></inline-formula>, named the cut-in value. We also show that the cut-in value depends on the LS's maximum allowed bias current. Finally, we discuss how the proposed framework can be extended to more than two users. It is also shown that significant battery life improvement can be achieved by employing the SLIPT method. Specifically, for a four user scenario the nearest user positioned at 5 m from the source gets a battery life improvement of 38.5% when the data rate is approximately 1.75 b/s/Hz and an improvement of 62% when the data rate is 1 b/s/Hz.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"403-418"},"PeriodicalIF":3.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975886","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}
Real-time underwater 3-D acoustic imaging employs various fast-beamforming methods that significantly reduce the computational cost. However, in the near-field region, these methods rely on a popular model based on the Fresnel approximation, which has a narrow field of view (FOV) boundary of approximately $26^circ$. The FOV of the near-field region is very limited compared with that of the far-field region. Therefore, in this study, an optimized subregion approach is proposed to eliminate the FOV limitation for fast beamforming to improve the FOV of the near-field region. First, the FOV is divided into subregions, and within each subregion, a linear approximation is adopted to simplify the time-delay expression, with the approximation error limited to a reasonable threshold. Furthermore, the least-squares method and coordinate rotation techniques are employed, and the FOV for each subregion is reshaped to an ideal shape. Subsequently, a nested nonuniform fast Fourier transform is proposed to implement fast beamforming, and subregions can be computed in parallel. The results demonstrate that the proposed approach overcomes the limited FOV that exists for near-field fast beamforming in 3-D acoustic imaging and has a computational complexity comparable with those of existing algorithms. In addition, this approach supports an irregular planar array and maintains a satisfactory performance.
{"title":"Expansion of Field of View for Near-Field Fast Beamforming in 3-D Acoustic Imaging Based on the Optimized Subregion Approach","authors":"Fei Wang;Xuesong Liu;Chenyi Lin;Xiang Gao;Boxuan Gu;Fan Zhou;Yaowu Chen","doi":"10.1109/JOE.2024.3463839","DOIUrl":"https://doi.org/10.1109/JOE.2024.3463839","url":null,"abstract":"Real-time underwater 3-D acoustic imaging employs various fast-beamforming methods that significantly reduce the computational cost. However, in the near-field region, these methods rely on a popular model based on the Fresnel approximation, which has a narrow field of view (FOV) boundary of approximately <inline-formula><tex-math>$26^circ$</tex-math></inline-formula>. The FOV of the near-field region is very limited compared with that of the far-field region. Therefore, in this study, an optimized subregion approach is proposed to eliminate the FOV limitation for fast beamforming to improve the FOV of the near-field region. First, the FOV is divided into subregions, and within each subregion, a linear approximation is adopted to simplify the time-delay expression, with the approximation error limited to a reasonable threshold. Furthermore, the least-squares method and coordinate rotation techniques are employed, and the FOV for each subregion is reshaped to an ideal shape. Subsequently, a nested nonuniform fast Fourier transform is proposed to implement fast beamforming, and subregions can be computed in parallel. The results demonstrate that the proposed approach overcomes the limited FOV that exists for near-field fast beamforming in 3-D acoustic imaging and has a computational complexity comparable with those of existing algorithms. In addition, this approach supports an irregular planar array and maintains a satisfactory performance.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"61-72"},"PeriodicalIF":3.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992931","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}
Semantic segmentation of forward-looking sonar (FLS) images plays a key role in the perception and interaction of autonomous underwater vehicles with the surrounding environment. Due to the strong noise and blurred object edges in sonar images, there is a high demand for the model's feature extraction and anti-interference ability. Currently, most methods are based on convolutional neural networks (CNNs), which are sensitive to local noise, and have a heavy computational burden, making them difficult to meet real-time requirements. This article re-examines CNNs and vision transformers, proposing a hybrid modeling-based network called HMSeg that combines both convolution modeling and attention modeling approaches for sonar image segmentation. In addition, a dynamic attention gate module is proposed to dynamically enhance feature maps with high-level features and eliminate interference. Furthermore, we propose a composite loss function to guide the model in extracting pure features and accurate semantic information. We present a new FLS image data set and conducted a series of experiments on a marine debris data set and a UATD-Seg data set. The results demonstrate that our proposed HMSeg achieves the best performance, proving its robustness and efficiency in different environments.
{"title":"Hybrid Modeling Based Semantic Segmentation of Forward-Looking Sonar Images","authors":"Yike Wang;Zhi Liu;Gongyang Li;Xiaofeng Lu;Xuefeng Liu;Hongwei Zhang","doi":"10.1109/JOE.2024.3467309","DOIUrl":"https://doi.org/10.1109/JOE.2024.3467309","url":null,"abstract":"Semantic segmentation of forward-looking sonar (FLS) images plays a key role in the perception and interaction of autonomous underwater vehicles with the surrounding environment. Due to the strong noise and blurred object edges in sonar images, there is a high demand for the model's feature extraction and anti-interference ability. Currently, most methods are based on convolutional neural networks (CNNs), which are sensitive to local noise, and have a heavy computational burden, making them difficult to meet real-time requirements. This article re-examines CNNs and vision transformers, proposing a hybrid modeling-based network called HMSeg that combines both convolution modeling and attention modeling approaches for sonar image segmentation. In addition, a dynamic attention gate module is proposed to dynamically enhance feature maps with high-level features and eliminate interference. Furthermore, we propose a composite loss function to guide the model in extracting pure features and accurate semantic information. We present a new FLS image data set and conducted a series of experiments on a marine debris data set and a UATD-Seg data set. The results demonstrate that our proposed HMSeg achieves the best performance, proving its robustness and efficiency in different environments.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"380-393"},"PeriodicalIF":3.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975888","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 : 2024-11-13DOI: 10.1109/JOE.2024.3467312
Rui Cao;Enrique M. Padilla;Yuxin Fang;Adrian H. Callaghan
We present a semi-automated image processing method, the continuous maximum gradient (CMG) method, for identifying the air–water interface in side-view digital images of unidirectional water waves in a glass-walled laboratory wave flume. In a manner similar to Canny edge detection, CMG exploits gradients in pixel intensity to identify the free surface, but also enforces an additional streamline constraint. This latter step is necessary to exclude signals from other features, such as wave gauges and water droplets on the glass, which also exhibit large intensity gradients. To demonstrate the performance and accuracy of CMG, we first compare its detection results with independent wave gauge measurements. The maximum difference in total spectral variance was found to be approximately 4%, while quantitative error metrics from a regression analysis yielded an $R^{2}$ value of 0.997 for the surface elevation time-series. We also compare the CMG detection results with imagery data from existing literature where excellent visual agreement is observed, confirming the broad applicability of the CMG method. The employment of CMG facilitates free surface measurements at a very high resolution (order of millimeters) which is essential for capturing the spatio-temporal wave-field evolution and obtaining instantaneous measurement of local wave shape.
{"title":"Identification of the Free Surface for Unidirectional Nonbreaking Water Waves From Side-View Digital Images","authors":"Rui Cao;Enrique M. Padilla;Yuxin Fang;Adrian H. Callaghan","doi":"10.1109/JOE.2024.3467312","DOIUrl":"https://doi.org/10.1109/JOE.2024.3467312","url":null,"abstract":"We present a semi-automated image processing method, the continuous maximum gradient (CMG) method, for identifying the air–water interface in side-view digital images of unidirectional water waves in a glass-walled laboratory wave flume. In a manner similar to Canny edge detection, CMG exploits gradients in pixel intensity to identify the free surface, but also enforces an additional streamline constraint. This latter step is necessary to exclude signals from other features, such as wave gauges and water droplets on the glass, which also exhibit large intensity gradients. To demonstrate the performance and accuracy of CMG, we first compare its detection results with independent wave gauge measurements. The maximum difference in total spectral variance was found to be approximately 4%, while quantitative error metrics from a regression analysis yielded an <inline-formula><tex-math>$R^{2}$</tex-math></inline-formula> value of 0.997 for the surface elevation time-series. We also compare the CMG detection results with imagery data from existing literature where excellent visual agreement is observed, confirming the broad applicability of the CMG method. The employment of CMG facilitates free surface measurements at a very high resolution (order of millimeters) which is essential for capturing the spatio-temporal wave-field evolution and obtaining instantaneous measurement of local wave shape.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"204-212"},"PeriodicalIF":3.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992993","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 : 2024-11-08DOI: 10.1109/JOE.2024.3458348
Xueyan Ding;Yixin Sui;Jianxin Zhang
Due to the complexity of underwater imaging environments, underwater images often suffer from blurriness, low contrast and color distortion, presenting a great challenge for underwater tasks. In this article, we propose a vector quantized underwater image enhancement network, which takes full advantage of generative adversarial networks and transformers through quantization. The proposed method consists of two parts: a vector quantized generative network and an axial flow-guided latent transformer. The vector quantized generative network first learns discrete content representations of underwater images through a vector quantized codebook. To facilitate deep feature extraction, an enhanced residual attention module that exploits the strengths of residual connection and channel-wise attention is introduced. After representing the content representation using codebook-indices, we use the axial flow-guided latent transformer to learn the content distribution in an autoregressive manner. The collaboration of generative adversarial networks and transformers assists in capturing both local and global dependencies in underwater images. Experimental results on publicly available data sets comprehensively validate the remarkable performance of the proposed method in underwater image enhancement tasks.
{"title":"Vector Quantized Underwater Image Enhancement With Transformers","authors":"Xueyan Ding;Yixin Sui;Jianxin Zhang","doi":"10.1109/JOE.2024.3458348","DOIUrl":"https://doi.org/10.1109/JOE.2024.3458348","url":null,"abstract":"Due to the complexity of underwater imaging environments, underwater images often suffer from blurriness, low contrast and color distortion, presenting a great challenge for underwater tasks. In this article, we propose a vector quantized underwater image enhancement network, which takes full advantage of generative adversarial networks and transformers through quantization. The proposed method consists of two parts: a vector quantized generative network and an axial flow-guided latent transformer. The vector quantized generative network first learns discrete content representations of underwater images through a vector quantized codebook. To facilitate deep feature extraction, an enhanced residual attention module that exploits the strengths of residual connection and channel-wise attention is introduced. After representing the content representation using codebook-indices, we use the axial flow-guided latent transformer to learn the content distribution in an autoregressive manner. The collaboration of generative adversarial networks and transformers assists in capturing both local and global dependencies in underwater images. Experimental results on publicly available data sets comprehensively validate the remarkable performance of the proposed method in underwater image enhancement tasks.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"136-149"},"PeriodicalIF":3.8,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992927","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 : 2024-11-08DOI: 10.1109/JOE.2024.3447877
Huafeng Wu;Kun Zhang;Xiaojun Mei;Linian Liang;Zhiheng Zhang;Feng Wang;Bing Han;Dezhi Han;Kuan-Ching Li
In extreme environments, such as polar oceans, where potential hazards like sea ice are prevalent, deploying autonomous surface vessel (ASV) can enhance operational efficiency and safeguard personnel. As these extreme environments necessitate higher performance standards, particularly in terms of path-following accuracy and control stability, we introduce in this research an ASV path-following control method predicated on an enhanced proportional–integral–derivative (PID) parameters tuning algorithm aimed at reducing path-following errors and bolstering control stability. First, the adaptive line-of-sight (ALOS) guidance algorithm is devised to determine the desired ASV heading by designing the forward-looking range adjustment strategy. Second, the improved sparrow search algorithm (ISSA) is proposed for PID parameters tuning. Since the lack of stability of the standard Sparrow Search Algorithm (SSA), the producer update strategy is modified, and the Brown–Levy mutation strategy is designed to improve the global search ability of the algorithm. Finally, the virtual ASV simulation platform is built, and the real-time PID controller is constructed by designing the PID real-time tuning strategy. The parameters of the Nomoto ship motion model are fitted in the simulation platform according to different marine environments, and the PID controller parameters are updated in real-time by ISSA to improve the path following accuracy. Experimental results of the marine environment simulation test and the real-world experiment show that the ALOS guidance algorithm can effectively generate the current desired rudder angle. The PID controller based on ISSA has the best performance in computer simulation. The average overshoot is 2.79%, and the average convergence time is 20.1 s. In the real-world experiment, the average path following error of ISSA Real-Time is reduced by 51.0% compared with that of SSA and 27.2% compared with that of ISSA. The improved control method can better satisfy the control requirements of the ASV, enhance control stability, and achieve more precise path following.
{"title":"Heuristic Strategy-Empowered Real-Time Path Following for Autonomous Surface Vessel With Adaptive Line-of-Sight Guidance","authors":"Huafeng Wu;Kun Zhang;Xiaojun Mei;Linian Liang;Zhiheng Zhang;Feng Wang;Bing Han;Dezhi Han;Kuan-Ching Li","doi":"10.1109/JOE.2024.3447877","DOIUrl":"https://doi.org/10.1109/JOE.2024.3447877","url":null,"abstract":"In extreme environments, such as polar oceans, where potential hazards like sea ice are prevalent, deploying autonomous surface vessel (ASV) can enhance operational efficiency and safeguard personnel. As these extreme environments necessitate higher performance standards, particularly in terms of path-following accuracy and control stability, we introduce in this research an ASV path-following control method predicated on an enhanced proportional–integral–derivative (PID) parameters tuning algorithm aimed at reducing path-following errors and bolstering control stability. First, the adaptive line-of-sight (ALOS) guidance algorithm is devised to determine the desired ASV heading by designing the forward-looking range adjustment strategy. Second, the improved sparrow search algorithm (ISSA) is proposed for PID parameters tuning. Since the lack of stability of the standard Sparrow Search Algorithm (SSA), the producer update strategy is modified, and the Brown–Levy mutation strategy is designed to improve the global search ability of the algorithm. Finally, the virtual ASV simulation platform is built, and the real-time PID controller is constructed by designing the PID real-time tuning strategy. The parameters of the Nomoto ship motion model are fitted in the simulation platform according to different marine environments, and the PID controller parameters are updated in real-time by ISSA to improve the path following accuracy. Experimental results of the marine environment simulation test and the real-world experiment show that the ALOS guidance algorithm can effectively generate the current desired rudder angle. The PID controller based on ISSA has the best performance in computer simulation. The average overshoot is 2.79%, and the average convergence time is 20.1 s. In the real-world experiment, the average path following error of ISSA Real-Time is reduced by 51.0% compared with that of SSA and 27.2% compared with that of ISSA. The improved control method can better satisfy the control requirements of the ASV, enhance control stability, and achieve more precise path following.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"307-323"},"PeriodicalIF":3.8,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992999","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 : 2024-11-05DOI: 10.1109/JOE.2024.3463700
David Campos Anchieta;John R. Buck
The background power spectral density (PSD) of underwater acoustic signals carries important information about the environment. However, loud transients from human or natural sources are outliers that undermine the precision and accuracy of PSD estimators, such as Welch's overlapped segment averaging (WOSA). Estimators based on order statistics (OSs), such as Schwock and Abadi's Welch Percentile (SAWP), avoid the loud transient bias by employing a normalized chosen OS of the periodograms as an estimator of the background PSD. This article proposes the truncated linear order statistics filter (TLOSF), a hybrid approach between WOSA and SAWP that estimates the background PSD with a weighted average of the OS below a chosen percentile. The TLOSF weights minimize the estimator variance subject to a constraint that the estimator remain unbiased. Including all of the OS below a threshold rank in the weighted average allows TLOSF to achieve a lower variance than the SAWP estimator, but still retain the same robustness against loud outliers. Experiments with synthetic data and underwater recordings demonstrate the improved performance of the TLOSF estimator over the SAWP and Welch estimators in the presence of outliers.
{"title":"Robust Power Spectral Density Estimation With a Truncated Linear Order Statistics Filter","authors":"David Campos Anchieta;John R. Buck","doi":"10.1109/JOE.2024.3463700","DOIUrl":"https://doi.org/10.1109/JOE.2024.3463700","url":null,"abstract":"The background power spectral density (PSD) of underwater acoustic signals carries important information about the environment. However, loud transients from human or natural sources are outliers that undermine the precision and accuracy of PSD estimators, such as Welch's overlapped segment averaging (WOSA). Estimators based on order statistics (OSs), such as Schwock and Abadi's Welch Percentile (SAWP), avoid the loud transient bias by employing a normalized chosen OS of the periodograms as an estimator of the background PSD. This article proposes the truncated linear order statistics filter (TLOSF), a hybrid approach between WOSA and SAWP that estimates the background PSD with a weighted average of the OS below a chosen percentile. The TLOSF weights minimize the estimator variance subject to a constraint that the estimator remain unbiased. Including all of the OS below a threshold rank in the weighted average allows TLOSF to achieve a lower variance than the SAWP estimator, but still retain the same robustness against loud outliers. Experiments with synthetic data and underwater recordings demonstrate the improved performance of the TLOSF estimator over the SAWP and Welch estimators in the presence of outliers.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"25-30"},"PeriodicalIF":3.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10742609","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992988","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 : 2024-11-05DOI: 10.1109/JOE.2024.3458108
John McConnell;Ivana Collado-Gonzalez;Paul Szenher;Brendan Englot
3-D situational awareness is critical for any autonomous system. However, when operating underwater, environmental conditions often dictate the use of acoustic sensors. These acoustic sensors are plagued by high noise and a lack of 3-D information in sonar imagery, motivating the use of an orthogonal pair of imaging sonars to recover 3-D perceptual data. Thus far, mapping systems in this area only use a subset of the available data at discrete timesteps and rely on object-level prior information in the environment to develop high-coverage 3-D maps. Moreover, simple repeating objects must be present to build high-coverage maps. In this work, we propose a submap-based mapping system integrated with a simultaneous localization and mapping system to produce dense, 3-D maps of complex unknown environments with varying densities of simple repeating objects. We compare this submapping approach to our previous works in this area, analyzing simple and highly complex environments, such as submerged aircraft. We analyze the tradeoffs between a submapping-based approach and our previous work leveraging simple repeating objects. We show where each method is well-motivated and where they fall short. Importantly, our proposed use of submapping achieves an advance in underwater situational awareness with wide aperture multibeam imaging sonar, moving toward generalized large-scale dense 3-D mapping capability for fully unknown complex environments.
{"title":"Large-Scale Dense 3-D Mapping Using Submaps Derived From Orthogonal Imaging Sonars","authors":"John McConnell;Ivana Collado-Gonzalez;Paul Szenher;Brendan Englot","doi":"10.1109/JOE.2024.3458108","DOIUrl":"https://doi.org/10.1109/JOE.2024.3458108","url":null,"abstract":"3-D situational awareness is critical for any autonomous system. However, when operating underwater, environmental conditions often dictate the use of acoustic sensors. These acoustic sensors are plagued by high noise and a lack of 3-D information in sonar imagery, motivating the use of an orthogonal pair of imaging sonars to recover 3-D perceptual data. Thus far, mapping systems in this area only use a subset of the available data at discrete timesteps and rely on object-level prior information in the environment to develop high-coverage 3-D maps. Moreover, simple repeating objects must be present to build high-coverage maps. In this work, we propose a submap-based mapping system integrated with a simultaneous localization and mapping system to produce dense, 3-D maps of complex unknown environments with varying densities of simple repeating objects. We compare this submapping approach to our previous works in this area, analyzing simple and highly complex environments, such as submerged aircraft. We analyze the tradeoffs between a submapping-based approach and our previous work leveraging simple repeating objects. We show where each method is well-motivated and where they fall short. Importantly, our proposed use of submapping achieves an advance in underwater situational awareness with wide aperture multibeam imaging sonar, moving toward generalized large-scale dense 3-D mapping capability for fully unknown complex environments.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"354-369"},"PeriodicalIF":3.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142976153","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 : 2024-11-05DOI: 10.1109/JOE.2024.3463702
Jianmin Lin;Chen Ji;Chenyu Ying;Wen Xu
The accurate monitoring and prediction of tropical cyclone (TC) intensity remains a challenging issue in meteorology due to the lack of reliable in situ observations during such severe weather events. Microseisms have recently been successfully used as a proxy to locate TC tracks. However, TC intensity inversions using microseisms have not been reported to date. Here, we present the first documented inversion of the relationship between the TC intensity and triggered seafloor microseisms using the continuous seismic waveforms from a large-scale ocean bottom seismometer array surrounding La Réunion Island, Southwest Indian Ocean, during the passage of TC Dumile (2013). A mathematical model of the relationship between the observed seafloor Rayleigh-wave microseism strengths and maximum sustained wind speed is constructed, with these two parameters exhibiting a power-law behavior. The wind speed inversion takes into account the lag time between TC processes and microseism excitation, as well as the compensation for propagation loss of the TC-generated microseisms, following an extensive examination of the optimal frequency band and dominant source regions. The inversion results yield an average error of about 0.85 m/s compared to the maximum sustained wind speed from the best-track data. The results demonstrated that seafloor microseisms can potentially be used for undersea remote sensing of ocean storms and TC intensity inversions, thereby providing an interdisciplinary complement to traditional atmospheric and oceanic observations.
由于缺乏可靠的现场观测，热带气旋强度的准确监测和预报仍然是气象学中一个具有挑战性的问题。微震最近被成功地用作定位TC轨迹的代理。然而，利用微地震反演TC强度迄今尚未见报道。在此，我们首次利用TC Dumile（2013）通过期间印度洋西南部La r union岛周围大型海底地震仪阵列的连续地震波，对TC强度与触发的海底微地震之间的关系进行了文献记录反演。建立了观测到的海底瑞利波微震强度与最大持续风速之间的数学模型，这两个参数表现为幂律行为。风速反演考虑了TC过程与微震激励之间的滞后时间，以及对TC产生的微震传播损失的补偿，并对最佳频带和优势震源区域进行了广泛的研究。与最佳路径数据的最大持续风速相比，反演结果产生的平均误差约为0.85 m/s。结果表明，海底微地震可以用于海洋风暴的海底遥感和TC强度反演，从而为传统的大气和海洋观测提供跨学科的补充。
{"title":"Tropical Cyclone Wind Speed Inversion Using Seafloor Rayleigh-Wave Microseisms","authors":"Jianmin Lin;Chen Ji;Chenyu Ying;Wen Xu","doi":"10.1109/JOE.2024.3463702","DOIUrl":"https://doi.org/10.1109/JOE.2024.3463702","url":null,"abstract":"The accurate monitoring and prediction of tropical cyclone (TC) intensity remains a challenging issue in meteorology due to the lack of reliable in situ observations during such severe weather events. Microseisms have recently been successfully used as a proxy to locate TC tracks. However, TC intensity inversions using microseisms have not been reported to date. Here, we present the first documented inversion of the relationship between the TC intensity and triggered seafloor microseisms using the continuous seismic waveforms from a large-scale ocean bottom seismometer array surrounding La Réunion Island, Southwest Indian Ocean, during the passage of TC Dumile (2013). A mathematical model of the relationship between the observed seafloor Rayleigh-wave microseism strengths and maximum sustained wind speed is constructed, with these two parameters exhibiting a power-law behavior. The wind speed inversion takes into account the lag time between TC processes and microseism excitation, as well as the compensation for propagation loss of the TC-generated microseisms, following an extensive examination of the optimal frequency band and dominant source regions. The inversion results yield an average error of about 0.85 m/s compared to the maximum sustained wind speed from the best-track data. The results demonstrated that seafloor microseisms can potentially be used for undersea remote sensing of ocean storms and TC intensity inversions, thereby providing an interdisciplinary complement to traditional atmospheric and oceanic observations.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"73-83"},"PeriodicalIF":3.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993001","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 : 2024-11-05DOI: 10.1109/JOE.2024.3436772
Han Liu;Suyue Wang;Qinghe Zhang;Fangqing Wen
Fully coherent X-band radar is a rapidly emerging tool for wave measurement. This article introduces a method for wave height inversion based on the sea surface coupled with broken-short waves and free waves using a fully coherent X-band radar. Initially, the Doppler spectrum characteristics from the coupled sea surface under vertical polarization are analyzed to obtain spatial–temporal velocity data. Subsequently, a 2-D Fourier transform is applied to the spatial–temporal matrix of velocities to estimate the wave number–frequency spectrum. The energy component produced by broken-short waves in the wave number–frequency spectrum is analyzed and partly filtered. Then, the processed wave number–frequency spectrum is integrated over the wave number domain to obtain the 1-D velocity spectrum. Subsequently, no calibration is required, and the wave height spectrum is estimated from the 1-D velocity spectrum. Finally, significant wave heights are derived from the zeroth moment of the wave height spectra. The method is validated through simulations and real data. An approximately 3-day data set that was collected using a shore-based fully coherent X-band radar, deployed along the coast of Shandong Province, China, is reanalyzed. Comparisons between the measurements of the radar and from the European Centre for Medium-Range Weather Forecasts (ECMWF) are conducted, and the radar-measured and the ECMWF's wave heights are in a reasonable agreement with a coherence coefficient of over 0.94. The results indicate that the proposed method is effective for wave height measurements under the coupled sea surface conditions using a coherent X-band radar.
{"title":"Wave Height Inversion on the Sea Surface Coupled With Broken-Short Waves and Free Waves Using a Fully Coherent X-Band Radar","authors":"Han Liu;Suyue Wang;Qinghe Zhang;Fangqing Wen","doi":"10.1109/JOE.2024.3436772","DOIUrl":"https://doi.org/10.1109/JOE.2024.3436772","url":null,"abstract":"Fully coherent <italic>X</i>-band radar is a rapidly emerging tool for wave measurement. This article introduces a method for wave height inversion based on the sea surface coupled with broken-short waves and free waves using a fully coherent <italic>X</i>-band radar. Initially, the Doppler spectrum characteristics from the coupled sea surface under vertical polarization are analyzed to obtain spatial–temporal velocity data. Subsequently, a 2-D Fourier transform is applied to the spatial–temporal matrix of velocities to estimate the wave number–frequency spectrum. The energy component produced by broken-short waves in the wave number–frequency spectrum is analyzed and partly filtered. Then, the processed wave number–frequency spectrum is integrated over the wave number domain to obtain the 1-D velocity spectrum. Subsequently, no calibration is required, and the wave height spectrum is estimated from the 1-D velocity spectrum. Finally, significant wave heights are derived from the zeroth moment of the wave height spectra. The method is validated through simulations and real data. An approximately 3-day data set that was collected using a shore-based fully coherent <italic>X</i>-band radar, deployed along the coast of Shandong Province, China, is reanalyzed. Comparisons between the measurements of the radar and from the European Centre for Medium-Range Weather Forecasts (ECMWF) are conducted, and the radar-measured and the ECMWF's wave heights are in a reasonable agreement with a coherence coefficient of over 0.94. The results indicate that the proposed method is effective for wave height measurements under the coupled sea surface conditions using a coherent <italic>X</i>-band radar.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 1","pages":"84-93"},"PeriodicalIF":3.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992928","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}
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