This study considers the data processing for acoustic cameras and achieves the generation of high-quality acoustic panoramas through image mosaicking. Thanks to high-resolution imaging, acoustic cameras are increasingly popular in ocean engineering. However, their narrow detection field of view makes it challenging to intuitively perceive marine environments. Generating large panoramas through mosaicking is a good way to solve this problem. Due to limitations such as low resolution, low signal-to-noise ratio, weak textures, and nonlinear distortions in acoustic images, most classic mosaicking pipelines do not perform well. This study proposes an adaptive mosaicking framework for acoustic cameras that integrates image denoising, feature matching, and mosaicking modules. It can generate large-area panoramas from overlapping acoustic camera images without any assumptions regarding the scenes. The overall process consists of three main steps: first, introduce a self-supervised denoising strategy to preprocess acoustic images to effectively remove complex noise; second, use a detector-free paradigm to achieve feature matching between adjacent acoustic images. This paradigm matches dense pixels in the high-level structure of images rather than relying on isolated geometric features, addressing the matching challenges in weak-texture areas. Third, design a mosaicking approach based on matching results to generate acoustic panoramas. This framework has been verified experimentally, and the results show that it canrobustly and effectively mosaic acoustic images, providing a novel reference and solution for underwater structures inspection in complex marine environments.
{"title":"Acoustic Camera-Based Adaptive Mosaicking Framework for Underwater Structures Inspection in Complex Marine Environments","authors":"Xiaoteng Zhou;Katsunori Mizuno;Yilong Zhang;Kenichiro Tsutsumi;Hideki Sugimoto","doi":"10.1109/JOE.2024.3423868","DOIUrl":"10.1109/JOE.2024.3423868","url":null,"abstract":"This study considers the data processing for acoustic cameras and achieves the generation of high-quality acoustic panoramas through image mosaicking. Thanks to high-resolution imaging, acoustic cameras are increasingly popular in ocean engineering. However, their narrow detection field of view makes it challenging to intuitively perceive marine environments. Generating large panoramas through mosaicking is a good way to solve this problem. Due to limitations such as low resolution, low signal-to-noise ratio, weak textures, and nonlinear distortions in acoustic images, most classic mosaicking pipelines do not perform well. This study proposes an adaptive mosaicking framework for acoustic cameras that integrates image denoising, feature matching, and mosaicking modules. It can generate large-area panoramas from overlapping acoustic camera images without any assumptions regarding the scenes. The overall process consists of three main steps: first, introduce a self-supervised denoising strategy to preprocess acoustic images to effectively remove complex noise; second, use a detector-free paradigm to achieve feature matching between adjacent acoustic images. This paradigm matches dense pixels in the high-level structure of images rather than relying on isolated geometric features, addressing the matching challenges in weak-texture areas. Third, design a mosaicking approach based on matching results to generate acoustic panoramas. This framework has been verified experimentally, and the results show that it canrobustly and effectively mosaic acoustic images, providing a novel reference and solution for underwater structures inspection in complex marine environments.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1549-1573"},"PeriodicalIF":3.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200200","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 : 2024-08-20DOI: 10.1109/JOE.2024.3423869
Karl D. von Ellenrieder;Marco Camurri
The use of automatic safety-critical control for uncrewed surface vessel (USV) survey, inspection and intervention can provide a computationally lightweight controller which guarantees that a minimum safe standoff distance to a target of interest is always maintained. We propose a trajectory tracking safety-critical controller for the closest safe approach of an underactuated USV with nonholonomic dynamic (acceleration) motion constraints to a target. A backstepping-based control law is designed using a relaxed control barrier function and an analytical convex optimization method. The stability of the controller is proven. Simulations of a USV approaching both stationary and moving targets are used to demonstrate implementation of the method. The performance of the proposed controller is compared with that of a nonlinear model predictive control (MPC) controller in simulation. The simulation results demonstrate that, while the tracking error of the proposed controller is higher than that of an MPC controller, it requires lower computational resources, suggesting it is a good candidate for use on small USVs with low computational power.
{"title":"Relaxed Control Barrier Function Based Control for Closest Approach by Underactuated USVs","authors":"Karl D. von Ellenrieder;Marco Camurri","doi":"10.1109/JOE.2024.3423869","DOIUrl":"https://doi.org/10.1109/JOE.2024.3423869","url":null,"abstract":"The use of automatic safety-critical control for uncrewed surface vessel (USV) survey, inspection and intervention can provide a computationally lightweight controller which guarantees that a minimum safe standoff distance to a target of interest is always maintained. We propose a trajectory tracking safety-critical controller for the closest safe approach of an underactuated USV with nonholonomic dynamic (acceleration) motion constraints to a target. A backstepping-based control law is designed using a relaxed control barrier function and an analytical convex optimization method. The stability of the controller is proven. Simulations of a USV approaching both stationary and moving targets are used to demonstrate implementation of the method. The performance of the proposed controller is compared with that of a nonlinear model predictive control (MPC) controller in simulation. The simulation results demonstrate that, while the tracking error of the proposed controller is higher than that of an MPC controller, it requires lower computational resources, suggesting it is a good candidate for use on small USVs with low computational power.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1301-1321"},"PeriodicalIF":3.8,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10639539","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438530","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 : 2024-08-16DOI: 10.1109/JOE.2024.3415753
Andrea Trucco
The study of the impact on the marine ecosystem of an offshore wind farm benefits from the knowledge of the underwater noise observed at a single turbine, as the wind speed varies. The calculation of the noise spectral average at a given wind speed requires many recordings, each acquired in a limited time interval: an extremely time-consuming process. This study investigated how to approach the spectral average using only very few noise recordings for each wind speed, leveraging supervised and unsupervised machine learning techniques. Three different prediction methods, based on mean and interpolation, principal component analysis (PCA), and nonnegative matrix factorization, in combination with four techniques for coefficient estimation as the wind varies, are tested. Prediction based on principal component analysis, combined with Gaussian process regression, outperforms other methods in all three case studies considered. The latter, in addition to the problem described above, include the prediction of the noise spectrum: at wind speeds where no noise recordings are available, and using a few recordings acquired at another (nominally identical) wind turbine.
{"title":"Predicting Underwater Noise Spectra Dominated by Wind Turbine Contributions","authors":"Andrea Trucco","doi":"10.1109/JOE.2024.3415753","DOIUrl":"10.1109/JOE.2024.3415753","url":null,"abstract":"The study of the impact on the marine ecosystem of an offshore wind farm benefits from the knowledge of the underwater noise observed at a single turbine, as the wind speed varies. The calculation of the noise spectral average at a given wind speed requires many recordings, each acquired in a limited time interval: an extremely time-consuming process. This study investigated how to approach the spectral average using only very few noise recordings for each wind speed, leveraging supervised and unsupervised machine learning techniques. Three different prediction methods, based on mean and interpolation, principal component analysis (PCA), and nonnegative matrix factorization, in combination with four techniques for coefficient estimation as the wind varies, are tested. Prediction based on principal component analysis, combined with Gaussian process regression, outperforms other methods in all three case studies considered. The latter, in addition to the problem described above, include the prediction of the noise spectrum: at wind speeds where no noise recordings are available, and using a few recordings acquired at another (nominally identical) wind turbine.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1675-1694"},"PeriodicalIF":3.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10638433","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200204","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 : 2024-08-16DOI: 10.1109/JOE.2024.3412227
Worakrit Thida;Roberto Li Voti;Sorasak Danworaphong
This study explored the use of top-view movies of propagating gravity water waves to reconstruct the underwater bed profile of shallow water bodies. Water waves of 2.8 and 3.1 Hz were generated by a microcontroller-driven flat flap in a wave flume of dimensions 0.48 × 1.80 × 0.40 m $^{3}$ . Three different bed profiles, i.e., sloped, stepped, and split surfaces, were used to imitate typical seabeds near shorelines. Top-view movies of the propagating waves were recorded and converted to spatial phase-speed images via video analysis. The phase speed images can be used to reconstruct the underwater bed profile using the dispersion relation of linear water waves. We also proposed a demodulation method to correct the phase-speed alteration due to wave interference. The correction method helped improve the mean average percentage error for depth profile predictions from 15% to 10% for the sloped profile and from 45% to 15% for the stepped profile. However, the approach was inferior for the split profile due to wall effects and complex interference patterns. This study suggests the proposed approach can determine the depth level around shorelines using time-evolution or video data with an adequate accuracy of 10% with minimal interference.
{"title":"Phase Speed Inversion for Shallow Water Bathymetry Mapping","authors":"Worakrit Thida;Roberto Li Voti;Sorasak Danworaphong","doi":"10.1109/JOE.2024.3412227","DOIUrl":"10.1109/JOE.2024.3412227","url":null,"abstract":"This study explored the use of top-view movies of propagating gravity water waves to reconstruct the underwater bed profile of shallow water bodies. Water waves of 2.8 and 3.1 Hz were generated by a microcontroller-driven flat flap in a wave flume of dimensions 0.48 × 1.80 × 0.40 m\u0000<inline-formula><tex-math>$^{3}$</tex-math></inline-formula>\u0000. Three different bed profiles, i.e., sloped, stepped, and split surfaces, were used to imitate typical seabeds near shorelines. Top-view movies of the propagating waves were recorded and converted to spatial phase-speed images via video analysis. The phase speed images can be used to reconstruct the underwater bed profile using the dispersion relation of linear water waves. We also proposed a demodulation method to correct the phase-speed alteration due to wave interference. The correction method helped improve the mean average percentage error for depth profile predictions from 15% to 10% for the sloped profile and from 45% to 15% for the stepped profile. However, the approach was inferior for the split profile due to wall effects and complex interference patterns. This study suggests the proposed approach can determine the depth level around shorelines using time-evolution or video data with an adequate accuracy of 10% with minimal interference.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1289-1300"},"PeriodicalIF":3.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200201","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 : 2024-08-16DOI: 10.1109/JOE.2024.3412218
Qiang Tu;Kefei Wu;En Cheng;Fei Yuan
Detecting acoustical signals arising from underwater gas leaks is crucial for monitoring greenhouse gas emissions from submarine vents using passive acoustical monitors. When gas bubbles intermittently generate, direct detection of the sound signals produced by these bubbles is an effective method for identifying underwater gas leaks. However, traditional energy detectors lack the capability to specifically detect bubble sound signals, making them susceptible to interference from marine environmental noise. Through an analysis of instantaneous bandwidth variation, we have identified two distinct feature components of bubble sound signals: short-term harmonic and wideband pulse. To address this, this article introduces a dual-feature-based bubble sound detection method. The method includes a bubble sound detector employing a sparse morphological component analysis (MCA) algorithm designed to extract these two feature components in both the time domain and time–frequency domain. The proposed feature-based detector demonstrates reliability and robustness against impulsive noise within ocean ambient noise. Furthermore, the proposed feature-based detector is applicable to the binary classification task of gas leak detection. Experimental results confirm the reliability and robustness of the proposed method in detecting underwater gas leaks.
{"title":"Dual-Feature-Based Bubble Sound Detection Method and Its Application in Passive Acoustical Detection of Underwater Gas Leakage","authors":"Qiang Tu;Kefei Wu;En Cheng;Fei Yuan","doi":"10.1109/JOE.2024.3412218","DOIUrl":"10.1109/JOE.2024.3412218","url":null,"abstract":"Detecting acoustical signals arising from underwater gas leaks is crucial for monitoring greenhouse gas emissions from submarine vents using passive acoustical monitors. When gas bubbles intermittently generate, direct detection of the sound signals produced by these bubbles is an effective method for identifying underwater gas leaks. However, traditional energy detectors lack the capability to specifically detect bubble sound signals, making them susceptible to interference from marine environmental noise. Through an analysis of instantaneous bandwidth variation, we have identified two distinct feature components of bubble sound signals: short-term harmonic and wideband pulse. To address this, this article introduces a dual-feature-based bubble sound detection method. The method includes a bubble sound detector employing a sparse morphological component analysis (MCA) algorithm designed to extract these two feature components in both the time domain and time–frequency domain. The proposed feature-based detector demonstrates reliability and robustness against impulsive noise within ocean ambient noise. Furthermore, the proposed feature-based detector is applicable to the binary classification task of gas leak detection. Experimental results confirm the reliability and robustness of the proposed method in detecting underwater gas leaks.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1657-1674"},"PeriodicalIF":3.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200206","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 : 2024-08-16DOI: 10.1109/JOE.2024.3408889
Yanwu Zhang;Brian Kieft;Brett W. Hobson;Quinn Shemet;Christina M. Preston;Christopher Wahl;Kathleen J. Pitz;Kelly J. Benoit-Bird;James M. Birch;Francisco P. Chavez;Christopher A. Scholin
Multiple autonomous underwater vehicles (AUVs) working in collaboration can achieve scientific goals more effectively than independently operated vehicles. In this article, we present a case of using two long-range AUVs (LRAUVs) for persistent environmental DNA (eDNA) sampling of a targeted feature. Each LRAUV was equipped with a third-generation environmental sample processor (3G-ESP), a robotic instrument for acquiring and processing water samples for molecular analysis. Each 3G-ESP can collect and process 60 samples. For continuous and persistent eDNA sampling of vertically migrating organisms at a targeted depth layer, we deployed two LRAUVs which alternately triggered the ESP, extending the total time of collecting samples. We developed a method of coordinated sampling by time shift and a collaborative sampling method that uses acoustic handshakes. In the time-shift method, each vehicle switched between two behaviors: sample collection at the targeted depth and spiraling over a large depth range to make contextual measurement. The second vehicle's mission started later than the first vehicle's by a time shift equal to the duration of one sampling event, such that at a given time one vehicle sampled at the targeted depth while the other vehicle spiraled up and down. In the acoustic-handshake method, the two LRAUVs exchanged sample-start and sample-end messages. On receiving vehicle #1’s sample-end message, vehicle #2 triggered a sampling event and transmitted a sample-start message to vehicle #1. Then, vehicle #1 waited for vehicle #2’s sample-end message before triggering the next sampling event, and so forth. The time-shift method is simple, whereas the acoustic-handshake method is accurate and adaptive. Both methods were demonstrated in experiments in Monterey Bay.
{"title":"Coordinated and Collaborative Sampling by Two Long-Range Autonomous Underwater Vehicles","authors":"Yanwu Zhang;Brian Kieft;Brett W. Hobson;Quinn Shemet;Christina M. Preston;Christopher Wahl;Kathleen J. Pitz;Kelly J. Benoit-Bird;James M. Birch;Francisco P. Chavez;Christopher A. Scholin","doi":"10.1109/JOE.2024.3408889","DOIUrl":"10.1109/JOE.2024.3408889","url":null,"abstract":"Multiple autonomous underwater vehicles (AUVs) working in collaboration can achieve scientific goals more effectively than independently operated vehicles. In this article, we present a case of using two long-range AUVs (LRAUVs) for persistent environmental DNA (eDNA) sampling of a targeted feature. Each LRAUV was equipped with a third-generation environmental sample processor (3G-ESP), a robotic instrument for acquiring and processing water samples for molecular analysis. Each 3G-ESP can collect and process 60 samples. For continuous and persistent eDNA sampling of vertically migrating organisms at a targeted depth layer, we deployed two LRAUVs which alternately triggered the ESP, extending the total time of collecting samples. We developed a method of coordinated sampling by time shift and a collaborative sampling method that uses acoustic handshakes. In the time-shift method, each vehicle switched between two behaviors: sample collection at the targeted depth and spiraling over a large depth range to make contextual measurement. The second vehicle's mission started later than the first vehicle's by a time shift equal to the duration of one sampling event, such that at a given time one vehicle sampled at the targeted depth while the other vehicle spiraled up and down. In the acoustic-handshake method, the two LRAUVs exchanged sample-start and sample-end messages. On receiving vehicle #1’s sample-end message, vehicle #2 triggered a sampling event and transmitted a sample-start message to vehicle #1. Then, vehicle #1 waited for vehicle #2’s sample-end message before triggering the next sampling event, and so forth. The time-shift method is simple, whereas the acoustic-handshake method is accurate and adaptive. Both methods were demonstrated in experiments in Monterey Bay.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1371-1382"},"PeriodicalIF":3.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10638321","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200203","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 : 2024-08-16DOI: 10.1109/JOE.2024.3410290
Easton Potokar;Kalliyan Lay;Kalin Norman;Derek Benham;Spencer Ashford;Randy Peirce;Tracianne B. Neilsen;Michael Kaess;Joshua G. Mangelson
Due to the difficulty and expense of underwater field trials, a high-fidelity underwater simulator is a necessity for testing and developing algorithms. To fill this need, we present HoloOcean, an open-source underwater simulator, built upon Unreal Engine 4 (UE4). HoloOcean comes equipped with multiagent support, various sensor implementations of common underwater sensors, and simulated communications support. Due to being built upon UE4, new environments are straightforward to add, enabling easy extensions to be built. HoloOcean is controlled via a simple Python interface, allowing simple installation via pip, and requiring few lines of code to execute simulations. Each agent is equipped with various control schemes and dynamics that can be customized via the Python interface. Also included is a novel sonar sensor framework that leverages an octree representation of the environment for efficient and realistic sonar imagery generation. In addition, to improve the authenticity of the imaging sonar simulation, we use a novel cluster-based multipath ray-tracing algorithm, various probabilistic noise models, and properties of reflecting surfaces. We also leverage the sonar simulation framework to simulate sidescan, single-beam, and multibeam profiling sonars.
{"title":"HoloOcean: A Full-Featured Marine Robotics Simulator for Perception and Autonomy","authors":"Easton Potokar;Kalliyan Lay;Kalin Norman;Derek Benham;Spencer Ashford;Randy Peirce;Tracianne B. Neilsen;Michael Kaess;Joshua G. Mangelson","doi":"10.1109/JOE.2024.3410290","DOIUrl":"10.1109/JOE.2024.3410290","url":null,"abstract":"Due to the difficulty and expense of underwater field trials, a high-fidelity underwater simulator is a necessity for testing and developing algorithms. To fill this need, we present HoloOcean, an open-source underwater simulator, built upon Unreal Engine 4 (UE4). HoloOcean comes equipped with multiagent support, various sensor implementations of common underwater sensors, and simulated communications support. Due to being built upon UE4, new environments are straightforward to add, enabling easy extensions to be built. HoloOcean is controlled via a simple Python interface, allowing simple installation via pip, and requiring few lines of code to execute simulations. Each agent is equipped with various control schemes and dynamics that can be customized via the Python interface. Also included is a novel sonar sensor framework that leverages an octree representation of the environment for efficient and realistic sonar imagery generation. In addition, to improve the authenticity of the imaging sonar simulation, we use a novel cluster-based multipath ray-tracing algorithm, various probabilistic noise models, and properties of reflecting surfaces. We also leverage the sonar simulation framework to simulate sidescan, single-beam, and multibeam profiling sonars.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1322-1336"},"PeriodicalIF":3.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200207","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 : 2024-08-13DOI: 10.1109/JOE.2024.3408891
Xiang Yu;Hong-De Qin;Zhong-Ben Zhu
For single-beacon navigation systems, the precision of the predetermined effective sound velocity (ESV) significantly affects the localization performance. However, the ESV between the pinger and receiver is time-varying, location-dependent, and difficult to determine accurately. ESV-setting errors induce large positioning errors and affect the practical applications of single-beacon navigation systems. Recently, unknown-ESV-based single-beacon navigation methods have been proposed to address the aforementioned issue, and their performances have been significantly better than those of known-ESV-based methods. This study aimed to conduct a theoretical analysis of the unknown-ESV-based single-beacon navigation methods in terms of observability. The local weak and global observabilities of an unknown-ESV-based single-beacon navigation system were investigated, and systems with and without ground-velocity measurements were considered. The observability of several common trajectories in underwater vehicles was summarized. Finally, a series of numerical simulations was conducted to validate the derived observability.
{"title":"Observability Analysis of a Single-Beacon Underwater Navigation Method With Unknown Effective Sound Velocity","authors":"Xiang Yu;Hong-De Qin;Zhong-Ben Zhu","doi":"10.1109/JOE.2024.3408891","DOIUrl":"10.1109/JOE.2024.3408891","url":null,"abstract":"For single-beacon navigation systems, the precision of the predetermined effective sound velocity (ESV) significantly affects the localization performance. However, the ESV between the pinger and receiver is time-varying, location-dependent, and difficult to determine accurately. ESV-setting errors induce large positioning errors and affect the practical applications of single-beacon navigation systems. Recently, unknown-ESV-based single-beacon navigation methods have been proposed to address the aforementioned issue, and their performances have been significantly better than those of known-ESV-based methods. This study aimed to conduct a theoretical analysis of the unknown-ESV-based single-beacon navigation methods in terms of observability. The local weak and global observabilities of an unknown-ESV-based single-beacon navigation system were investigated, and systems with and without ground-velocity measurements were considered. The observability of several common trajectories in underwater vehicles was summarized. Finally, a series of numerical simulations was conducted to validate the derived observability.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1634-1646"},"PeriodicalIF":3.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200208","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 : 2024-08-13DOI: 10.1109/JOE.2024.3412202
Yukang Xue;Xiangzhao Qin;Yahong Rosa Zheng
This article extends the data dithering reuse (DDR) method to waveform modulation for underwater acoustic communications and enables postexperimental cross evaluation between single-carrier modulation (SCM) and orthogonal frequency-division multiplexing (OFDM). The proposed DDR method reuses the data from the original experimental scheme (OES) to evaluate a new scheme under test with different waveform modulations by adding dithering and reverse dithering, respectively, to the transmitted and received OES data. The proposed DDR method consists of three steps: 1) data block preparation; 2) waveform dithering; and 3) channel estimation and reverse dithering. OFDM signals with cyclic prefix or zero-padding guard intervals can be evaluated with the SCM of different constellation orders and vice versa. We demonstrate the effectiveness of the proposed cross-evaluation method using multiple-input multiple-output (MIMO) field measurements from the undersea 2008 Surface Processes and Acoustic Communications Experiment, compared to the original experimental data sets and existing residual prediction error (RPE)-enhanced replay simulations. The MIMO soft-decision frequency-domain Turbo equalization is used to detect both the SCM and OFDM schemes. The results confirm that the average bit error rate (BER) and the BER distribution predicted by the proposed DDR method are closer to the OES evaluation and are more robust than the RPE-enhanced replay simulation.
{"title":"Cross Evaluation of Waveform Modulation Schemes Using Postexperimental Field Data","authors":"Yukang Xue;Xiangzhao Qin;Yahong Rosa Zheng","doi":"10.1109/JOE.2024.3412202","DOIUrl":"10.1109/JOE.2024.3412202","url":null,"abstract":"This article extends the data dithering reuse (DDR) method to waveform modulation for underwater acoustic communications and enables postexperimental cross evaluation between single-carrier modulation (SCM) and orthogonal frequency-division multiplexing (OFDM). The proposed DDR method reuses the data from the original experimental scheme (OES) to evaluate a new scheme under test with different waveform modulations by adding dithering and reverse dithering, respectively, to the transmitted and received OES data. The proposed DDR method consists of three steps: 1) data block preparation; 2) waveform dithering; and 3) channel estimation and reverse dithering. OFDM signals with cyclic prefix or zero-padding guard intervals can be evaluated with the SCM of different constellation orders and vice versa. We demonstrate the effectiveness of the proposed cross-evaluation method using multiple-input multiple-output (MIMO) field measurements from the undersea 2008 Surface Processes and Acoustic Communications Experiment, compared to the original experimental data sets and existing residual prediction error (RPE)-enhanced replay simulations. The MIMO soft-decision frequency-domain Turbo equalization is used to detect both the SCM and OFDM schemes. The results confirm that the average bit error rate (BER) and the BER distribution predicted by the proposed DDR method are closer to the OES evaluation and are more robust than the RPE-enhanced replay simulation.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1622-1633"},"PeriodicalIF":3.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142200209","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 : 2024-07-24DOI: 10.1109/JOE.2024.3401779
Songzuo Liu;Honglu Yan;Lu Ma;Yanan Liu;Xue Han
Due to the high cost of sea trials and the variability of sea states, the duration of experiments is usually too short to fully verify underwater acoustic communication (UAC) performance in a real-ocean environment. Moreover, traditional UAC channel simulators also face issues of inaccurate environmental parameters or mismatched statistical models. To tackle these challenges, we propose UACC-GAN, a data-driven stochastic channel simulator for UAC, offering an innovative solution for channel data augmentation. UACC-GAN uses the generative adversarial network model to learn the latent space of the measured channel data set and then maps the random sampling points in this space into a new time-varying impulse response (TVIR). Our simulator is validated using the small-scale WATERMARK data set collected at sea. The results indicate that the generated TVIR has a realistic delay–Doppler spread and can reproduce time-varying delay path characteristics. The cumulative distribution of multiple 0-D properties also proves the realism of the entire distribution of the generated channel data set. In addition, by relying on the continuity of the latent space, UACC-GAN generates channel characteristics with random fluctuations, such as Doppler spectrum shape, delay energy distribution, and tap covariance, which contributes to more diverse communication testing conditions. Finally, we pass frequency-hopping spread spectrum and orthogonal frequency-division multiplexing communication signals through the generated and measured channels. The comparable results of simulated bit error rate (BER) and actual BER underline the value of the UACC-GAN simulator for communication system design and testing.
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