• Title/Summary/Keyword: underwater target

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Study on Unmanned Hybrid Unmanned Surface Vehicle and Unmanned Underwater Vehicle System

  • Jin, Han-Sol;Cho, Hyunjoon;Lee, Ji-Hyeong;Jiafeng, Huang;Kim, Myung-Jun;Oh, Ji-Youn;Choi, Hyeung-Sik
    • Journal of Ocean Engineering and Technology
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    • v.34 no.6
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    • pp.475-480
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    • 2020
  • Underwater operating platforms face difficulties regarding power supply and communications. To overcome these difficulties, this study proposes a hybrid surface and underwater vehicle (HSUV) and presents the development of the platform, control algorithms, and results of field tests. The HSUV is capable of supplying reliable power to the unmanned underwater vehicle (UUV) and obtaining data in real time by using a tether cable between the UUV and the unmanned surface vehicle (USV). The HSUV uses global positioning system (GPS) and ultra-short base line sensors to determine the relative location of the UUV. Way point (WP) and dynamic positioning (DP) algorithms were developed to enable the HSUV to perform unmanned exploration. After reaching the target point using the WP algorithm, the DP algorithm enables USV to maintain position while withstanding environmental disturbances. To ensure the navigation performance at sea, performance tests of GPS, attitude/heading reference system, and side scan sonar were conducted. Based on these results, manual operation, WP, and DP tests were conducted at sea. WP and DP test results and side scan sonar images during the sea trials are presented.

Machine Learning-based MCS Prediction Models for Link Adaptation in Underwater Networks (수중 네트워크의 링크 적응을 위한 기계 학습 기반 MCS 예측 모델 적용 방안)

  • Byun, JungHun;Jo, Ohyun
    • Journal of Convergence for Information Technology
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    • v.10 no.5
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    • pp.1-7
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    • 2020
  • This paper proposes a link adaptation method for Underwater Internet of Things (IoT), which reduces power consumption of sensor nodes and improves the throughput of network in underwater IoT network. Adaptive Modulation and Coding (AMC) technique is one of link adaptation methods. AMC uses the strong correlation between Signal Noise Rate (SNR) and Bit Error Rate (BER), but it is difficult to apply in underwater IoT as it is. Therefore, we propose the machine learning based AMC technique for underwater environments. The proposed Modulation Coding and Scheme (MCS) prediction model predicts transmission method to achieve target BER value in underwater channel environment. It is realistically difficult to apply the predicted transmission method in real underwater communication in reality. Thus, this paper uses the high accuracy BER prediction model to measure the performance of MCS prediction model. Consequently, the proposed AMC technique confirmed the applicability of machine learning by increase the probability of communication success.

Experimental Study on Underwater Docking of a Visual Servoing Autonomous Underwater Vehicle (비쥬얼 서보 자율무인잠수정의 수중 도킹에 관한 실험적 연구)

  • Lee, Pan-Mook;Jeon, Bong-Hwan;Lee, Ji-Hong;Kim, Sea-Moon;Hong, Young-Hwan
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2003.05a
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    • pp.89-93
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    • 2003
  • The Korea Research Institute of Ships and Ocean Engineering (KRISO), the ocean engineering branch of KORDI, has designed and manufactured a model of an autonomous underwater vehicle (AUV) to test underwater docking. This paper introduces the AUV model, ASUM, equipped with a visual servo control system to dock into an underwater station with a camera and motion sensors. To make a visual servoing AUV, this paper implemented the visual servo control system designed with an augmented state equation, which was composed of the optical flow model of a camera and the equation of the AUV's motion. The system design and the hardware configuration of ASUM are presented in this paper. A small long baseline acoustic positioning system was developed to monitor and record the AUV's position for the experiment in the Ocean Engineering Basin of KRISO, KORDI. ASUM recognizes the target position by processing the captured image for the lights, which are installed around the end of the cone-type entrance of the duct. Unfortunately, experiments are not yet conducted when we write this article. The authors will present the results for the docking test of the AUV in near future.

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Research on an Engagement Level Underwater Weapon System Model with Neyman-Pearson Detector (Neyman-Pearson 표적 탐지기를 적용한 수중 무기체계 교전수준 모델 개발 연구)

  • Cho, Hyunjin;Kim, Wan-Jin;Kim, Sanghun;Yang, Hocheol;Lee, Hee Kwang
    • Journal of the Korea Society for Simulation
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    • v.28 no.2
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    • pp.89-95
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    • 2019
  • This paper introduces the simulation concepts and technical approach of underwater weapon system performance analysis simulator, especially focused on probabilistic target detection concepts. We calculated the signal excess (SE) value using SONAR equation, then derived the probability density function(PDF) for target presence($H_1$) or absence($H_0$) cases, respectively. With the Neyman-Pearson detector criterion, we got the probability of detection($P_D$) while satisfying the given probability of false alarm($P_{FA}$). At every instance of simulation, target detection is decided in the probabilistic perspective. With the proposed detection implementation, we improved the model fidelity so that it could support the tactical decision during the operation.

Experimental Study on Propulsion Characteristic of Autonomous Intervention ROV (자율작업용 원격운용잠수정의 추진 특성에 관한 실험 연구)

  • Yeu, Taekyeong;Lee, Yoongeon;Chae, Junbo;Yoon, Sukmin;Lee, Yeongjun
    • Journal of Ocean Engineering and Technology
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    • v.33 no.5
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    • pp.454-461
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    • 2019
  • In autonomous interventions using an underwater vehicle with a manipulator, grasping based on target detection and recognition is one of the core technologies. To complete an autonomous grasping task, the vehicle body approaches the target closely and then holds it through operating the end-effector of the manipulator, while the vehicle maintains its position and attitude without unstable motion. For vehicle motion control, it is very important to identify the hydrodynamic parameters of the underwater vehicle, including the propulsion force. This study examined the propulsion characteristics of the autonomous intervention ROV developed by KRISO, because there is a difference between the real exerted force and the expected force. First, the mapping between the input signal and thrusting force for each underwater thruster was obtained through a water tank experiment. Next, the real propulsion forces and moments of the ROV exerted by thrusting forces were directly measured using an F/T (force/torque) sensor attached to the ROV. Finally, the differences between the measured and expected values were confirmed.

Anti-washout Grouts for Underwater Sealing of Karst Cavities and Construction Research Tendencies (수중 불분리성 그라우트 개발 기술 동향)

  • Baluch, Khaqan;Kim, Jung-Gyu;Kim, Jong-Gwan;Yu, Ji-Yun;Yang, Hyung-Sik
    • Explosives and Blasting
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    • v.38 no.4
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    • pp.46-52
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    • 2020
  • Although anti-washout grouts are used extensively in underwater targets, major constraints continue to be associated with their use. These include poor bonding strength, poor pumpability, and loss of high strength in everyday engineering applications. In this study, based on the literature pertaining to self-compacted, non-dispersive, anti-washout grouts, a review of research trends in anti-washout grouts for underwater construction and sealing of karst cavities was carried out in order to determine the problems faced in this field. Grouts used under water suffer a loss of strength and bonding strength in comparison to grouts cast in air. Researchers are designing high-viscosity grouts to overcome the inrush of water and seal karst cavities; however, in doing so, they have inadvertently caused serious problems pertaining to the pumpability of these grouts and concretes in deep target locations. Thus, the majority of the anti-washout grouts and concretes that have been developed are not applicable to deep target environments, instead being suitable for only near-surface targets.

Underwater Target Discrimination using Sequential Testings and Data Fusion (순차 검증과 자료융합을 이용한 수중 표적 판별)

  • Kwak, Eun-Joo
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.657-659
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    • 1998
  • In this paper we discuss an algorithm to discriminate a target under track against multiple acoustic counter-measure (ACM) sources, based on sequential testings of multiple hypotheses. The ACM sources are separated from the target under track and generate, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target tracking and to help the true target evade a pursuer. The proposed algorithm uses as a test statistic a function of both the sequences of processed waveform signature and the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting positions of the ACM sources. Numerical experiments on various scenarios show that the proposed algorithm discriminates the target faster with a higher probability of success than the algorithm using only the innovation sequences from extended Kalman filters.

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Development of side attack guidance law for an underwater vehicle (수중 운동체를 위한 측면 공격 유도 기법)

  • 이보형;이장규;한형석;김병수
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.533-539
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    • 1993
  • In this paper, two side-attack guidance laws for an underwater vehicle are considered. In order to find the guidance command, we first make use of the optimal guidance law with terminal impact angle constraint. Secondly, the optimal solution of tracking problem is used. This paper shows some brief theory which is used in deriving the side-attack guidance laws, and the method of computing these guidance laws. Simulations on underwater vehicle for a constant moving target prove that the suggested side-attack guidance laws have enhanced side attack performance over the optimal guidance law with miss distance weighting only. Furthermore, from simulation results. we conclude that the guidance law using the optimal solution of tracking problem is more efficient for the side-attack guidance than the optimal guidance law with terminal impact angle constraint.

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Control for Manipulator of an Underwater Robot Using Meta Reinforcement Learning (메타강화학습을 이용한 수중로봇 매니퓰레이터 제어)

  • Moon, Ji-Youn;Moon, Jang-Hyuk;Bae, Sung-Hoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.1
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    • pp.95-100
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    • 2021
  • This paper introduces model-based meta reinforcement learning as a control for the manipulator of an underwater construction robot. Model-based meta reinforcement learning updates the model fast using recent experience in a real application and transfers the model to model predictive control which computes control inputs of the manipulator to reach the target position. The simulation environment for model-based meta reinforcement learning is established using MuJoCo and Gazebo. The real environment of manipulator control for underwater construction robot is set to deal with model uncertainties.

Underwater target discrimination using geometry of ACM tracks (음향교란 항적의 기하학적 특성을 이용한 수중 표적 판별)

  • 정영헌;전상운;홍선목
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.3
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    • pp.110-119
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    • 1998
  • In this paper we discuss an algorithm to discriminate a garget under track against multiple acoustic counter-measure (ACM) sources, based on sequential testings of multiple hypotheses. The ACM sources are separated from the target under track and generate, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target tracking and to help the true target evade a pursuer. The proposed algorithm uses as a test statistic a function of the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting positions of the ACM sources. results of numerical experimenats are presented to show a performance profile of the proposed algorithm.

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