• Title/Summary/Keyword: Sonar sensor

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Convergence of Initial Estimation Error in a Hybrid Underwater Navigation System with a Range Sonar (초음파 거리계를 갖는 수중복합항법시스템의 초기오차 수렴 특성)

  • LEE PAN MOOK;JUN BONG HUAN;KIM SEA MOON;CHOI HYUN TAEK;LEE CHONG MOO;KIM KI HUN
    • Journal of Ocean Engineering and Technology
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    • v.19 no.6 s.67
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    • pp.78-85
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    • 2005
  • Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.

Sources separation of passive sonar array signal using recurrent neural network-based deep neural network with 3-D tensor (3-D 텐서와 recurrent neural network기반 심층신경망을 활용한 수동소나 다중 채널 신호분리 기술 개발)

  • Sangheon Lee;Dongku Jung;Jaesok Yu
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.4
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    • pp.357-363
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    • 2023
  • In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.

Time-Varying Subspace Tracking Algorithm for Nonstationary DOA Estimation in Passive Sensor Array

  • Lim, Junseok;Song, Joonil;Pyeon, Yongkug;Sung, Koengmo
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.1E
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    • pp.7-13
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    • 2001
  • In this paper we propose a new subspace tracking algorithm based on the PASTd (Projection Approximation Subspace Tracking with deflation). The algorithm is obtained via introducing the variable forgetting factor which adapts itself to the time-varying subspace environments. The tracking capability of the proposed algorithm is demonstrated by computer simulations in an abruptly changing DOA scenario. The estimation results of the variable forgetting factor PASTd(VFF-PASTd) outperform those of the PASTd in the nonstationary case as well as in the stationary case.

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A Study on Fuzzy Controller for Autonomous Mobile Robot (자율 이동 로보트의 퍼지 제어기에 관한 연구)

  • 주영훈;황희수;고재원;김성권;황금찬;우광방
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1071-1084
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    • 1992
  • In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

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Dynamic Analysis of Piezoelectric Sonar Transducer (압전재료를 이용한 수중음향 센서의 동적 해석)

  • Yu, Nanhui;Kim, Heung-Soo;Kim, Jae-Hwan;Roh, Yong-Rae;Joh, Chee-Young
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.196-200
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    • 2005
  • Piezoelectric underwater acoustic transducer is a kind of device for underwater detection working as not only an actuator but also a sensor. The technique that can predict acoustical characteristics of transducer is important for robust design of transducer in harsh underwater environment. This paper represents the dynamic analysis of piezoelectric acoustic transducers based on finite element method through USAP software. Two dimensional model of Tonpilz transducer and three dimensional model of Flextensional transducer are generated for the dynamic analysis and some results obtained by USAP are compared with those by ANSYS.

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Reflexive Autonomous Vehicle Control Using Neural Networks (신경회로망을 이용한 반사적인 무인차 제어)

  • Kim, Yoo-Seok;Lee, Jang-Gyu
    • Proceedings of the KIEE Conference
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    • 1991.07a
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    • pp.888-891
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    • 1991
  • In this paper, we have shown a new approach of neural networks for mobile robot motion control under an indoor refracted environment. The vehicle has two powered wheels and four passive casters which support a free motion. And it also uses sonar sensors, infrared sensors, Internal odometer, and contact sensors. Two experiments were conducted to demonstrate our objectives. The first one is that the vehicle executes a reflexive motor control to maintain a constant distance to the boundary. The second one is that as well as the boundary following, the vehicle makes a block obstacle avoidance during its path. Without prior knowledge of external environment. we have accomplished the tasks by employing a simple, reactive stimulus-response neural network scheme associating sensor data with the vehicle's action.

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PZT5 spherical hydrophone simulation using a coupled FE-BE method (결합형 유한요소-경계요소 기법을 활용한 PZT5 구형 수중 수파기 시뮬레이션)

  • Jarng, Soon-Suck
    • Journal of Sensor Science and Technology
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    • v.7 no.6
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    • pp.377-385
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    • 1998
  • This paper describes the application of a coupled finite element-boundary element method to obtain the steady-state response of a hydrophone. The particular structure considered is a flooded piezoelectric spherical shell. The hydrophone is three-dimensionally simulated to transduce an incident plane acoustic pressure onto the outer surface of the sonar spherical shell to electrical potentials on inner and outer surfaces of the shell. The acoustic field formed from the scattered sound pressure is also simulated. And the displacement of the shell caused by the externally incident acoustic pressure is shown in temporal motion. The coupled FE-BE method is described in detail.

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Position Estimation of an Underground Acoustic Source by a Passive Sonar System

  • Jarng, Soon-Suck
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06e
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    • pp.133-136
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    • 1998
  • The aim of the work described in this paper is to develop a complex underground acoustic system which detects and locates the origin of an underground hammering sound using an array of six hydrophones located about 100m underground. Two different methods for the sound localization will be presented, a time-delay method and a power-attenuation method. In the time-delay method, the cross correlation of the signals received from the array of sensor sis used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure f the distances of the source from the sensors.

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Self Localization of Mobile Robot Using Sonar Sensor and Grid Map Making (초음파 센서와 격자 지도 생성을 통한 자율 이동 로봇의 자기 위치 추정)

  • Kim, Ji-Min;Jeong, Tae-Won
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2426-2428
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    • 2004
  • 자율이동로봇에 있어서 기본적이면서도 가장 중요한 문제 중의 하나는 자신의 위치를 추정하는 것이다. 만약 로봇 자신이 어디에 있는지 알지 못한다면 효과적으로 로봇의 동작을 계획할 수도 없을 뿐 아니라, 목표물을 찾을 수도 없으며 목표에 도달하는 데 있어서도 상당한 문제가 생기게 된다. 이미 로봇의 자기 위치추정 문제에 대해서는 GPS, 시각, 레이져, 초음파 센서등을 이용한 많은 기술들이 개발된 상태이다. 하지만 각각의 방법들에 있어서 정확성의 향상은 하드웨어 비용의 증가와 추가 전력을 고려해야 하는 등의 문제를 가져오게 되었다. 문제의 핵심은 저렴하면서도 손쉽고 정확한 값을 갖는 알고리즘을 개발하는 데 있다고 할 수 있는 것이다. 본 논문에서는 초음파 센서를 이용하여 이러한 문제에 대한 만족할 만한 답을 얻고자 한다.

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Vision-Based Robot Manipulator for Grasping Objects (물체 잡기를 위한 비전 기반의 로봇 메뉴플레이터)

  • Baek, Young-Min;Ahn, Ho-Seok;Choi, Jin-Young
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.331-333
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    • 2007
  • Robot manipulator is one of the important features in service robot area. Until now, there has been a lot of research on robot" manipulator that can imitate the functions of a human being by recognizing and grasping objects. In this paper, we present a robot arm based on the object recognition vision system. We have implemented closed-loop control that use the feedback from visual information, and used a sonar sensor to improve the accuracy. We have placed the web-camera on the top of the hand to recognize objects. We also present some vision-based manipulation issues and our system features.

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