• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.12
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• pp.84-89
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• 2014

This paper proposes the new multiple signal processing monitoring sensor for the marine installation. The recent marine technology is focused on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. For these marine applications to be available, however, the provision of precise location information using monitoring sensor is essential. In this paper, the multiple signal processing circuit for obtaining the precise location information of marine installation sensor is developed and analyzed. The performance characteristics for obtaining the location information of marine installation sensor is analyzed. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably excellent performance for the monitoring for the marine installation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.809-811
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• 2015

In this paper, for the purpose of providing high data rate services, the multi-hop frame structure is designed for the underwater acoustic (UWA) short-range system which is proposed as a part of ocean surveillance and tracking network (OSTN). Under the measured underwater channel environment, the link-level system performance are also evaluated. Simulation results show not only the packet error rate (PER) comparisons, but the optimal modulation and coding scheme (MCS) levels for the orthogonal frequency division multiplexing (OFDM) based short-range UWA communications network.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.3-9
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• 2017

Due to difficulties of continuous electric power provision to underwater communication nodes, the efficient power usage is highly required in underwater network protocol. In this paper, we studied the energy efficient MAC(Medium Access Control) protocol for underwater network supporting mobile nodes such as UUV(Unmanned Underwater Vehicle) and AUV(Autonomous Underwater Vehicle). The mobile nodes could waste the electric power in vain when the receiver moves out of the radio propagation coverage during the data exchange and thus the transmitted data fails in reaching the receiver. Expecially, such a failure is much more obvious in underwater acoustic channels since the propagation delay is about $10^5$ times slower than in terrestrial radio channels. This proposed mobility-MAC controls the data dropping stochastically in the Dropping Zone by considering the receiver's location and moving velocity. In conclusion, this selective dropping method not only improves latency and throughput by reducing invalid droppings but also boosts power efficiency by valid droppings.

• Journal of Information Processing Systems
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• v.6 no.1
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• pp.53-66
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• 2010

The energy efficiency is a key design issue to improve the lifetime of the underwater sensor networks (UWSN) consisting of sensor nodes equipped with a small battery of limited energy resource. In this paper, we apply a hexagon tessellation with an ideal cell size to deploy the underwater sensor nodes for two-dimensional UWSN. Upon this setting, we propose an enhanced hybrid transmission method that forwards data packets in a mixed transmission way based on location dependent direct transmitting or uniform multi-hop forwarding. In order to select direct transmitting or uniform multi-hop forwarding, the proposed method applies the threshold annulus that is defined as the distance between the cluster head node and the base station (BS). Our simulation results show that the proposed method enhances the energy efficiency compared with the existing multi-hop forwarding methods and hybrid transmission methods

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1484-1486
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• 2001

In this study, The underwater object recognition using ultrasonic sensor fabricated with porous PZT-Polymer 3-3 type composites and invariant moment vector and SOFM(Self Organizing Feature Map) neural networks are presented. The recognition rates for the training data and the testing data were 98% and 94%, respectively.

• Proceedings of the KIEE Conference
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• 1997.07d
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• pp.1370-1372
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• 1997

In this study, 3-D underwater object recognition using ultrasonic sensor fabricated with porous piezoelectric ceramics and SCL(Simple Competitive Learning) neural networks are presented. The recognition rates for the training data and the testing dara were 96 and 93%, respectively.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2330-2332
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• 2000

In this study, 3-D underwater object recognition using ultrasonic sensor fabricated with PZT-Polymer 1-3 type composites and invariant moment vector and SOFM(Self Organizing Feature Map) neural networks are presented. The recognition rates for the training data and the testing data were 99% and 93%, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.621-624
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• 2017

In this paper, we propose a protocol synchronizing to packet trains in a underwater acoustic networks with limitations such as long propagation delay, low data rate, high packet loss. The proposed protocol employs an one-way communication scheme to calculate packet arrival time differences of consecutively transferred packets and minimizes uncertain variation effect of long propagation delay. Simulation results shows the superiority of our protocol, compared with a previously proposed one under the given network conditions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.82-86
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• 2008

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.399-404
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• 2011

For the underwater wireless sensor networks, we propose the packet transmission method which distinguishes more important packet than others. Because the ocean underwater transmission environments are extremely unstable, we use SON(Self Organizing Network) techniques to adapt to the constantly varying underwater acoustic communication channels and randomly deployed sensor nodes. Especially we suppose two kinds of packets which have different priorities, and through the simulations we show that high priority packets arrive at the source node faster than lower priority packets with a proposed scheme.