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Underwater acoustic communication and the general performance evaluation criteria
Jian-guo HUANG, Han WANG, Cheng-bing HE, Qun-fei ZHANG, Lian-you JING
Front. Inform. Technol. Electron. Eng. 2018, 19 (8): 951-971.
https://doi.org/10.1631/FITEE.1700775
Driven by the huge demand to explore oceans, underwater wireless communications have been rapidly developed in the past few decades. Due to the complex physical characteristics of water, acoustic wave is the only media available for underwater wireless communication at any distance. As a result, underwater acoustic communication (UAC) is the major research field in underwater wireless communication. In this paper, characteristics of underwater acoustic channels are first introduced and compared with terrestrial communication to demonstrate the difficulties in UAC research. To give a general impression of the UAC, current important research areas are mentioned. Furthermore, different principal modulation-based schemes for short- and medium-range communications with high data rates are investigated and summarized. To evaluate the performance of UAC systems in general, three criteria are presented based on the research publications and our years of experience in high-rate short- to medium-range communications. These three criteria provide useful tools to generally guide the design and evaluate the performance of underwater acoustic communication systems.
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An underwater acoustic direct sequence spread spectrum communication system using dual spread spectrum code
Lan-jun LIU, Jian-fen LI, Lin ZHOU, Peng ZHAI, Hao ZHAO, Jiu-cai JIN, Zhi-chao LV
Front. Inform. Technol. Electron. Eng. 2018, 19 (8): 972-983.
https://doi.org/10.1631/FITEE.1700746
With the goal of achieving high stability and reliability to support underwater point-to-point communications and code division multiple access (CDMA) based underwater networks, a direct sequence spread spectrum based underwater acoustic communication system using dual spread spectrum code is proposed. To solve the contradictions between the information data rate and the accuracy of Doppler estimation, channel estimation, and frame synchronization, a data frame structure based on dual spread spectrum code is designed. A long spread spectrum code is used as the training sequence, which can be used for data frame detection and synchronization, Doppler estimation, and channel estimation. A short spread spectrum code is used to modulate the effective information data. A delay cross-correlation algorithm is used for Doppler estimation, and a correlation algorithm is used for channel estimation. For underwater networking, each user is assigned a different pair of spread spectrum codes. Simulation results show that the system has a good anti-multipath, anti-interference, and anti-Doppler performance, the bit error rate can be smaller than 10−6 when the signal-to-noise ratio is larger than −10 dB, the data rate can be as high as 355 bits/s, and the system can be used in the downlink of CDMA based networks.
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Underwater video transceiver designs based on channel state information and video content
Rong-xin ZHANG, Xiao-li MA, De-qing WANG, Fei YUAN, En CHENG
Front. Inform. Technol. Electron. Eng. 2018, 19 (8): 984-998.
https://doi.org/10.1631/FITEE.1700767
Underwater hostile channel conditions challenge video transmission designs. The current designs often treat video coding and transmission schemes as individual modules. In this study, we develop an adaptive transceiver with channel state information (CSI) by taking into account the importance of video components and channel conditions. The design is more effective than the traditional ones. However, in practical systems, perfect CSI may not be available. Therefore, we compare the imperfect CSI case with existing schemes, and validate the effectiveness of our design through simulations and measured channels in terms of a better peak signal-to-noise ratio and a higher video structural similarity index.
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Energy-efficient localization and target tracking via underwater mobile sensor networks
Hua-yan CHEN, Mei-qin LIU, Sen-lin ZHANG
Front. Inform. Technol. Electron. Eng. 2018, 19 (8): 999-1012.
https://doi.org/10.1631/FITEE.1700598
Underwater mobile sensor networks (UMSNs) with free-floating sensors are more suitable for understanding the immense underwater environment. Target tracking, whose performance depends on sensor localization accuracy, is one of the broad applications of UMSNs. However, in UMSNs, sensors move with environmental forces, so their positions change continuously, which poses a challenge on the accuracy of sensor localization and target tracking. We propose a high-accuracy localization with mobility prediction (HLMP) algorithm to acquire relatively accurate sensor location estimates. The HLMP algorithm exploits sensor mobility characteristics and the multistep Levinson-Durbin algorithm to predict future positions. Furthermore, we present a simultaneous localization and target tracking (SLAT) algorithm to update sensor locations based on measurements during the process of target tracking. Simulation results demonstrate that the HLMP algorithm can improve localization accuracy significantly with low energy consumption and that the SLAT algorithm can further decrease the sensor localization error. In addition, results prove that a better localization accuracy will synchronously improve the target tracking performance.
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Underwater docking of an under-actuated autonomous underwater vehicle: system design and control implementation
Bo LI, Yuan-xin XU, Shuang-shuang FAN, Wen XU
Front. Inform. Technol. Electron. Eng. 2018, 19 (8): 1024-1041.
https://doi.org/10.1631/FITEE.1700382
Underwater docking greatly facilitates and extends operation of an autonomous underwater vehicle (AUV) without the support of a surface vessel. Robust and accurate control is critically important for docking an AUV into a small underwater funneltype dock station. In this paper, a docking system with an under-actuated AUV is presented, with special attention paid to control algorithm design and implementation. For an under-actuated AUV, the cross-track error can be controlled only via vehicle heading modulation, so both the cross-track error and heading error have to be constrained to achieve successful docking operations, while the control problem can be even more complicated in practical scenarios with the presence of unknown ocean currents. To cope with the above issues, a control scheme of a three-hierarchy structure of control loops is developed, which has been embedded with online current estimator/compensator and effective control parameter tuning. The current estimator can evaluate both horizontal and vertical current velocity components, based only on the measurement of AUV’s velocity relative to the ground; in contrast, most existing methods use the measurements of both AUV’s velocities respectively relative to the ground and the water column. In addition to numerical simulation, the proposed docking scheme is fully implemented in a prototype AUV using MOOS-IvP architecture. Simulation results show that the current estimator/compensator works well even in the presence of lateral current disturbance. Finally, a series of sea trials are conducted to validate the current estimator/compensator and the whole docking system. The sea trial results show that our control methods can drive the AUV into the dock station effectively and robustly.
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Automatic analysis of deep-water remotely operated vehicle footage for estimation of Norway lobster abundance
Ching Soon TAN, Phooi Yee LAU, Paulo L. CORREIA, Aida CAMPOS
Front. Inform. Technol. Electron. Eng. 2018, 19 (8): 1042-1055.
https://doi.org/10.1631/FITEE.1700720
Underwater imaging is being used increasingly by marine biologists as a means to assess the abundance of marine resources and their biodiversity. Previously, we developed the first automatic approach for estimating the abundance of Norway lobsters and counting their burrows in video sequences captured using a monochrome camera mounted on trawling gear. In this paper, an alternative framework is proposed and tested using deep-water video sequences acquired via a remotely operated vehicle. The proposed framework consists of four modules: (1) preprocessing, (2) object detection and classification, (3) object-tracking, and (4) quantification. Encouraging results were obtained from available test videos for the automatic video-based abundance estimation in comparison with manual counts by human experts (ground truth). For the available test set, the proposed system achieved 100% precision and recall for lobster counting, and around 83% precision and recall for burrow detection.
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9 articles
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