Impact of MAC Delay on AUV Localization: Underwater Localization Based on Hyperbolic Frequency Modulation Signal

Kim, Sungryul; Yoo, Younghwan

doi:10.3390/s18020356

Cited by 7 publications

(8 citation statements)

References 23 publications

(21 reference statements)

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“…Where the graph is divided into a special k − tree graph, such as the P-LOC problem can be solved in polynomial time for any fixed k ≥ 1. Authors in [88] investigate the impact of MAC delay and nodes mobility on the localization accuracy. The MAC delay occurs when anchor nodes communicate between each other through the MAC protocol to avoid packets collision.…”

Section: Localization In Uwsnsmentioning

confidence: 99%

See 1 more Smart Citation

Underwater Wireless Sensor Networks: A Survey on Enabling Technologies, Localization Protocols, and Internet of Underwater Things

et al. 2019

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Underwater communication remains a challenging technology via communication cables and the cost of underwater sensor network (UWSN) deployment is still very high. As an alternative, underwater wireless communication has been proposed and have received more attention in the last decade. Preliminary research indicated that the Radio Frequency (RF) and Magneto-Inductive (MI) communication achieve higher data rate in the near field communication. The optical communication achieves good performance when limited to the line-of-sight positioning. The acoustic communication allows long transmission range. However, it suffers from transmission losses and time-varying signal distortion due to its dependency on environmental properties. These latter are salinity, temperature, pressure, depth of transceivers, and the environment geometry. This paper is focused on both the acoustic and magneto-inductive communications, which are the most used technologies for underwater networking. Such as acoustic communication is employed for applications requiring long communication range while the MI is used for real-time communication. Moreover, this paper highlights the trade-off between underwater properties, wireless communication technologies, and communication quality. This can help the researcher community by providing clear insight for further research.

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Section: Localization In Uwsnsmentioning

confidence: 99%

“…MAC delay joined to the mobility impact can affect localization performance. The study conducted on [88] reveals that the combination of fast node move and longer MAC delay results in a great localization error. To cope with this issue, a localization method combined with multiple access system is proposed.…”

Section: Localization In Uwsnsmentioning

confidence: 99%

Underwater Wireless Sensor Networks: A Survey on Enabling Technologies, Localization Protocols, and Internet of Underwater Things

et al. 2019

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“…Multi-AUV systems are subject to communication delays in underwater environments. Some researchers 15 –17 proposed a time compensation method or a method of enhancing the time delay controller for the communication delay problem, which reduces the influence of underwater acoustic communication delay on the hunting alliance. The literature 18,19 use the optimized communication topology to coordinate the multi-AUV hunting alliance, which can carry out hunting tasks in the communication delay environment, and improve the reliability of the algorithm.…”

Section: Related Workmentioning

confidence: 99%

Multiautonomous underwater vehicle consistent collaborative hunting method based on generative adversarial network

Cai

Sun

2020

International Journal of Advanced Robotic Systems

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The time-varying ocean currents and the delay of underwater acoustic communication have caused the uncertainty of single autonomous underwater vehicle (AUV) tracking target and the inconsistency of multi-AUV coordination, which make it difficult for multiple AUVs to form a hunting alliance. To solve the above problems, this article proposes the multi-AUV consistent collaborative hunting method based on generative adversarial network (GAN). Firstly, the three-dimensional (3D) kinematic model of AUV is established for the underwater 3D environment. Secondly, combined with the Laplacian matrix, the topology of the hunting alliance in the ideal environment is established, and the control rate of AUV is calculated. Finally, using the GAN network model, the control relationship after environmental interference is used as the input of the generative model. The control rate in the ideal environment is used as the comparison object of the discriminative model. Using the iterative training of GAN to generate a control rate that adapts to the current interference environment and combining multi-AUV topological hunting model to achieve successful hunting of noncooperative target, the experimental results show that the algorithm reduces the average hunting time to 62.53 s and the success rate of hunting is increased to 84.69%, which is 1.17% higher than the particle swarm optimization-constant modulus algorithm (PSO-CMA) algorithm.

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“…Sensors 2020, 20,1943 4 of 18 distance from source nodes. We adopt a multi-layer-based AUV formation topology according to their relative distance.…”

Section: Adaptive Communication Protocolmentioning

confidence: 99%

“…However, the data for transmission is so great that wireless communication was used to assist acoustic communication during the sea trials of two AUVs' cooperative missions [18]. Guo, Frater, and Ryan [19] proposed an adaptive propagation-delay tolerant media access control (MAC) [20] protocol for an underwater acoustic communication network. The protocol performs an improved handshaking with destination using RTS and CTS frames before transmitting the actual data frame to improve the communication efficiency.…”

Section: Introductionmentioning

confidence: 99%

Multibody System-Based Adaptive Formation Scheme for Multiple Under-Actuated AUVs

Huang

Tang

Zhang

et al. 2020

Sensors

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Underwater vehicles’ coordination and formation have attracted increasing attention since they have great potential for real-world applications. However, such vehicles are usually under-actuated and with very limited communication capabilities. On the basis of the multibody system concept, a multiple autonomous underwater vehicle formation and communication link framework has been established with an adaptive and radial basis function (RBF) strategy. For acoustic communication, a packets transmission scheme with topology and protocol has been investigated on the basis of an acoustic communication framework and transmission model. Moreover, the cooperative localization errors caused by packet loss are estimated through reinforcement learning radial basis function neural networks. Furthermore, in order to realize formation cruising, an adaptive RBF formation scheme with magnitude reduced multi-layered potential energy functions has been designed on the basis of a time-delayed network framework. Finally, simulations and experiments have been extensively performed to validate the effectiveness of the proposed methods.

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Impact of MAC Delay on AUV Localization: Underwater Localization Based on Hyperbolic Frequency Modulation Signal

Cited by 7 publications

References 23 publications

Underwater Wireless Sensor Networks: A Survey on Enabling Technologies, Localization Protocols, and Internet of Underwater Things

Underwater Wireless Sensor Networks: A Survey on Enabling Technologies, Localization Protocols, and Internet of Underwater Things

Multiautonomous underwater vehicle consistent collaborative hunting method based on generative adversarial network

Multibody System-Based Adaptive Formation Scheme for Multiple Under-Actuated AUVs

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