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15 pages, 4386 KiB

Open AccessArticle

A Novel Embedded Side Information Transmission Scheme Based on Polar Code for Peak-to-Average Power Ratio Reduction in Underwater Acoustic OFDM Communication System

by Siyu Xing, Bo Wei, Yanting Yu and Xiaodong Gong

Sensors 2024, 24(22), 7200; https://doi.org/10.3390/s24227200 - 10 Nov 2024

Viewed by 567

Abstract

In this paper, we proposed an embedded side information (SI) transmission scheme based on polar code construction for PAPR reduction using the PTS scheme in the underwater Acoustic (UWA) Orthogonal Frequency Division Multiplexing (OFDM) communication system. We use polar codes due to the [...] Read more.

In this paper, we proposed an embedded side information (SI) transmission scheme based on polar code construction for PAPR reduction using the PTS scheme in the underwater Acoustic (UWA) Orthogonal Frequency Division Multiplexing (OFDM) communication system. We use polar codes due to the ability of the arbitrarily designed code rate. Additionally, polar codes can be employed to establish a nested code structure consisting of multiple subsets. The SI bits can be embedded in a polar codeword by exploiting these features. Thus, the approach does not occupy existing data rates or cause additional loss in data transmission rates. At the same time, it embeds m-sequence into the polar code as an indicator vector for the blind SI detector, which makes the blind SI detector able to autonomously discriminate SI at the receiver. Simulation and tank experiment results indicate that the proposed embedded SI transmission scheme has the potential to significantly decrease the likelihood of whole-symbol error caused by SI errors. Meanwhile, the proposed PTS scheme eliminates the need to wait for the entire packet to be received before obtaining the SI, thereby preventing waste of data storage devices and ensuring real-time performance of the Underwater Acoustic Communication (UAC) OFDM system. This achieves symbol-level real-time calculation for the system. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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26 pages, 11126 KiB

Open AccessArticle

Infrared Bilateral Polarity Ship Detection in Complex Maritime Scenarios

by Dongming Lu, Longyin Teng, Jiangyun Tan, Mengke Wang, Zechen Tian and Guihua Wang

Sensors 2024, 24(15), 4906; https://doi.org/10.3390/s24154906 - 29 Jul 2024

Viewed by 717

Abstract

In complex maritime scenarios where the grayscale polarity of ships is unknown, existing infrared ship detection methods may struggle to accurately detect ships among significant interference. To address this issue, this paper first proposes an infrared image smoothing method composed of Grayscale Morphological [...] Read more.

In complex maritime scenarios where the grayscale polarity of ships is unknown, existing infrared ship detection methods may struggle to accurately detect ships among significant interference. To address this issue, this paper first proposes an infrared image smoothing method composed of Grayscale Morphological Reconstruction (GMR) and a Relative Total Variation (RTV). Additionally, a detection method considering the grayscale uniformity of ships and integrating shape and spatiotemporal features is established for detecting bright and dark ships in complex maritime scenarios. Initially, the input infrared images undergo opening (closing)-based GMR to preserve dark (bright) blobs with the opposite suppressed, followed by smoothing the image with the relative total variation model to reduce clutter and enhance the contrast of the ship. Subsequently, Maximally Stable Extremal Regions (MSER) are extracted from the smoothed image as candidate targets, and the results from the bright and dark channels are merged. Shape features are then utilized to eliminate clutter interference, yielding single-frame detection results. Finally, leveraging the stability of ships and the fluctuation of clutter, true targets are preserved through a multi-frame matching strategy. Experimental results demonstrate that the proposed method outperforms ITDBE, MRMF, and TFMSER in seven image sequences, achieving accurate and effective detection of both bright and dark polarity ship targets. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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21 pages, 10212 KiB

Open AccessArticle

Robust Learning with Noisy Ship Trajectories by Adaptive Noise Rate Estimation

by Haoyu Yang, Mao Wang, Zhihao Chen, Kaiming Xiao, Xuan Li and Hongbin Huang

Sensors 2023, 23(15), 6723; https://doi.org/10.3390/s23156723 - 27 Jul 2023

Viewed by 1005

Abstract

Ship trajectory classification is of great significance for shipping analysis and marine security governance. However, in order to cover up their illegal fishing or espionage activities, some illicit ships will forge the ship type information in the Automatic Identification System (AIS), and this [...] Read more.

Ship trajectory classification is of great significance for shipping analysis and marine security governance. However, in order to cover up their illegal fishing or espionage activities, some illicit ships will forge the ship type information in the Automatic Identification System (AIS), and this label noise will significantly impact the algorithm’s classification accuracy. Sample selection is a common and effective approach in the field of learning from noisy labels. However, most of the existing methods based on sample selection need to determine the noise rate of the data through prior means. To address these issues, we propose a noise rate adaptive learning mechanism that operates without prior conditions. This mechanism is integrated with the robust training paradigm JoCoR (joint training with co-regularization), giving rise to a noise rate adaptive learning robust training paradigm called A-JoCoR. Experimental results on real-world trajectories provided by the Danish Maritime Authority verified the effectiveness of A-JoCoR. It not only realizes the adaptive learning of the data noise rate during the training process, but also significantly improves the classification performance compared with the original method. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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14 pages, 6283 KiB

Open AccessArticle

A Novel Thermal Tactile Sensor Based on Micro Thermoelectric Generator for Underwater Flow Direction Perception

by Changxin Liu, Nanxi Chen, Guangyi Xing, Runhe Chen, Tong Shao, Baichuan Shan, Yilin Pan and Minyi Xu

Sensors 2023, 23(12), 5375; https://doi.org/10.3390/s23125375 - 6 Jun 2023

Cited by 6 | Viewed by 2058

Abstract

Underwater vehicles can operate independently in the exploitation of marine resources. However, water flow disturbance is one of the challenges underwater vehicles must face. The underwater flow direction sensing method is a feasible way to overcome the challenges but faces difficulties such as [...] Read more.

Underwater vehicles can operate independently in the exploitation of marine resources. However, water flow disturbance is one of the challenges underwater vehicles must face. The underwater flow direction sensing method is a feasible way to overcome the challenges but faces difficulties such as integrating the existing sensors with underwater vehicles and high-cost maintenance fees. In this research, an underwater flow direction sensing method based on the thermal tactility of the micro thermoelectric generator (MTEG) is proposed, with the theoretical model established. To verify the model, a flow direction sensing prototype is fabricated to carry out experiments under three typical working conditions. The three typical flow direction conditions are: condition No. 1, in which the flow direction is parallel to the x-axis; condition No. 2, in which the flow direction is at an angle of 45° to the x-axis; and condition No. 3, which is a variable flow direction condition based on condition No. 1 and condition No. 2. According to the experimental data, the variations and orders of the prototype output voltages under three conditions fit the theoretical model, which means the prototype can identify the flow direction of three conditions. Besides, experimental data show that in the flow velocity range of 0~5 m/s and the flow direction variation range of 0~90°, the prototype can accurately identify the flow direction in 0~2 s. The first time utilizing MTEG on underwater flow direction perception, the underwater flow direction sensing method proposed in this research is cheaper and easier to be applied on the underwater vehicles than traditional underwater flow direction sensing methods, which means it has great application prospects in underwater vehicles. Besides, the MTEG can utilize the waste heat of the underwater vehicle battery as the energy source to achieve self-powered work, which greatly enhances its practical value. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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9 pages, 3929 KiB

Open AccessArticle

Experimental Study of Deep Submersible Structure Defect Monitoring Based on Flexible Interdigital Transducer Surface Acoustic Wave Technology

by Zhongjun Ding, Zhiliang Feng, Hongyu Li, Dejian Meng, Yi Zhang and Dewei Li

Sensors 2023, 23(3), 1184; https://doi.org/10.3390/s23031184 - 20 Jan 2023

Cited by 3 | Viewed by 1693

Abstract

In view of the shortage of structural defect monitoring methods for deep submersibles, numerical simulation and experimental research on underwater SAW propagation based on interdigital transducers are carried out in this paper. PVDF interdigital transducer (PVDF-IDT) has shown considerable potential in the application [...] Read more.

In view of the shortage of structural defect monitoring methods for deep submersibles, numerical simulation and experimental research on underwater SAW propagation based on interdigital transducers are carried out in this paper. PVDF interdigital transducer (PVDF-IDT) has shown considerable potential in the application of structural health monitoring because of its micro size, soft material characteristics, and the characteristics of long-term bonding on the surface of the tested structure. In order to realize the application of IDT on submersible or underwater structures, it is necessary to understand the influence of underwater environment on IDTs with different structures. The underwater attenuation of IDT with 2–5 mm wavelength and the underwater attenuation of Lamb (A0 mode) wave on a 4 mm thick titanium alloy plate is obtained through COMSOL software simulation. The experimental verification shows that the simulation results match with the actual situation, which proves that COMSOL software can accurately calculate the acoustic attenuation of surface waves at the solid–liquid interface. At the same time, the underwater attenuation of IDT with different structures is very different, providing important design parameters for the underwater interdigital transducer. In this paper, it is found that the Lamb wave has significant advantages over the Rayleigh wave in the health monitoring of underwater thin plate structures. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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21 pages, 7245 KiB

Open AccessArticle

Feature Attribution Analysis to Quantify the Impact of Oceanographic and Maneuverability Factors on Vessel Shaft Power Using Explainable Tree-Based Model

by Donghyun Kim, Melia Putri Handayani, Sangbong Lee and Jihwan Lee

Sensors 2023, 23(3), 1072; https://doi.org/10.3390/s23031072 - 17 Jan 2023

Cited by 7 | Viewed by 2218

Abstract

A vessel sails above the ocean against sea resistance, such as waves, wind, and currents on the ocean surface. Concerning the energy efficiency issue in the marine ecosystem, assigning the right magnitude of shaft power to the propeller system that is needed to [...] Read more.

A vessel sails above the ocean against sea resistance, such as waves, wind, and currents on the ocean surface. Concerning the energy efficiency issue in the marine ecosystem, assigning the right magnitude of shaft power to the propeller system that is needed to move the ship during its operations can be a contributive study. To provide both desired maneuverability and economic factors related to the vessel’s functionality, this research studied the shaft power utilization of a factual vessel operational data of a general cargo ship recorded during 16 months of voyage. A machine learning-based prediction model that is developed using Random Forest Regressor achieved a 0.95 coefficient of determination considering the oceanographic factors and additional maneuver settings from the noon report data as the model’s predictors. To better understand the learning process of the prediction model, this study specifically implemented the SHapley Additive exPlanations (SHAP) method to disclose the contribution of each predictor to the prediction results. The individualized attributions of each important feature affecting the prediction results are presented. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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18 pages, 15510 KiB

Open AccessArticle

Dynamic Maritime Traffic Pattern Recognition with Online Cleaning, Compression, Partition, and Clustering of AIS Data

by Yuanqiang Zhang and Weifeng Li

Sensors 2022, 22(16), 6307; https://doi.org/10.3390/s22166307 - 22 Aug 2022

Cited by 14 | Viewed by 3493

Abstract

Maritime traffic pattern recognition plays a major role in intelligent transportation services, ship monitoring, route planning, and other fields. Facilitated by the establishment of terrestrial networks and satellite constellations of the automatic identification system (AIS), large quantities of spatial and temporal information make [...] Read more.

Maritime traffic pattern recognition plays a major role in intelligent transportation services, ship monitoring, route planning, and other fields. Facilitated by the establishment of terrestrial networks and satellite constellations of the automatic identification system (AIS), large quantities of spatial and temporal information make ships’ paths trackable and are useful in maritime traffic pattern research. The maritime traffic pattern may vary with changes in the traffic environment, so the recognition method of the maritime traffic pattern should be adaptable to changes in the traffic environment. To achieve this goal, a dynamic maritime traffic pattern recognition method is presented using AIS data, which are cleaned, compressed, partitioned, and clustered online. Old patterns are removed as expired trajectories are deleted, and new patterns are created as new trajectories are added. This method is suitable for processing massive stream data. Experiments show that when the marine traffic route changes due to the navigation environment, the maritime traffic pattern adjusts automatically. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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13 pages, 4226 KiB

Open AccessArticle

A Cantilever Beam-Based Triboelectric Nanogenerator as a Drill Pipe Transverse Vibration Energy Harvester Powering Intelligent Exploitation System

by Zhenhui Lian, Qunyi Wang, Chuanqing Zhu, Cong Zhao, Qiang Zhao, Yan Wang, Zhiyuan Hu, Ruijiang Xu, Yukai Lin, Tianyu Chen, Xiangyu Liu, Xiaoyan Xu, Ling Liu, Xiu Xiao and Minyi Xu

Sensors 2022, 22(11), 4287; https://doi.org/10.3390/s22114287 - 4 Jun 2022

Cited by 7 | Viewed by 2445

Abstract

Measurement While Drilling (MWD) is the most commonly used real-time information acquisition technique in offshore intelligent drilling, its power supply has always been a concern. Triboelectric nanogenerators have been shown to harvest low-frequency vibrational energy in the environment and convert it into electricity [...] Read more.

Measurement While Drilling (MWD) is the most commonly used real-time information acquisition technique in offshore intelligent drilling, its power supply has always been a concern. Triboelectric nanogenerators have been shown to harvest low-frequency vibrational energy in the environment and convert it into electricity to power small sensors and electrical devices. This work proposed a cantilever-beam-based triboelectric nanogenerator (CB-TENG) for transverse vibration energy harvesting of a drill pipe. The CB-TENG consists of two vibrators composed of spring steel with PTFE attached and Al electrodes. The structurally optimized CB-TENG can output a peak power of 2.56 mW under the vibration condition of f = 3.0 Hz and A = 50 mm, and the electrical output can be further enhanced with the increased vibration parameters. An array-type vibration energy harvester integrated with eight CB-TENGs is designed to fully adapt to the interior of the drill pipe and improve output performance. The device can realize omnidirectional vibration energy harvesting in the two-dimensional plane with good robustness. Under the typical vibration condition, the short-circuit current and the peak power can reach 49.85 μA and 30.95 mW, respectively. Finally, a series of demonstration experiments have been carried out, indicating the application prospects of the device. Full article

(This article belongs to the Special Issue Advanced Sensing Technologies for Marine Intelligent Systems)

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