• 센서학회지
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• 제25권5호
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• pp.333-336
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• 2016

In this study, a beta monitoring sensor was developed as a part of basic research for quantitative beta monitoring underwater, and its performance was evaluated using a calibration source. A beta detection sensor was manufactured by using SiPM(silicon photomultiplier) and $CaF_2$:Eu, YAG:Ce, YAP:Ce scintillator. A large-area light guide was introduced to improve beta-ray detection efficiency. As calibration sources, the Beta source $^{90}Sr$, which is the main fission product of a nuclear accident, and the gamma source $^{137}Cs$ are used. In the performance evaluation, it is confirmed that scintillator $CaF_2:Eu$ gives the highest beta-ray detection response. Compared to gamma ray, beta-ray detection responsivity and detection efficiency are verified. Therefore, this study is expected to contribute to basic research in the development of an underwater beta-ray monitoring system.

• International Journal of Ocean System Engineering
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• 제1권3호
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• pp.165-170
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• 2011

In this paper, for the accurate estimation of the position and orientation of the UUV (unmanned underwater vehicle), an AHRS (Attitude Heading Reference System) was developed using the IMU (inertial measurement unit) sensor which provides information on acceleration and orientation in the object coordinate and the initial alignment algorithm and the E-KF (extended Kalman Filter). The initial position and orientation of the UUV are estimated using the initial alignment algorithm with 3-axis acceleration and geomagnetic information of the IMU sensor. The position and orientation of the UUV are estimated using the AHRS composed of 3-axis acceleration, velocity, and geomagnetic information and the E-KF. For the performance test of the orientation estimation of the AHRS, a testbed using IMU sensor(ADIS16405) and DSP28335 coded with an E-KF algorithm was developed and its performance was verified through tests.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.107-112
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• 2013

In this paper, we discuss a 3-dimensional localization sensor node using EM waves (Electromagnetic waves) with RSSI (Received Signal Strength Indicator). Generally EM waves cannot be used in underwater environment, because the signal is highly attenuated by the water medium according to the distance. Although the signal quickly reduces in underwater, the reducing tendency is very clear and uniform. Hence EM waves have possibility as underwater distance sensors. The authors have verified the possibility by theory and several experiments, and developed calibration methods in case of linear and planer environment. For 3-dimensional localization in underwater, it must be known antenna's radiation pattern property in electric plane(called E-plane). In this paper, we proceed experiments to verify attenuation tendency with z axis movement, PLF (Polarization Loss Factor) and ILF (Inclination Loss Factor) with its theoretical approach.

• Journal of Advanced Marine Engineering and Technology
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• 제39권5호
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• pp.522-526
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• 2015

Generally, underwater unmanned vehicle have adopted an inertial navigation system (INS), dead reckoning (DR), acoustic navigation and geophysical navigation techniques as the navigation method because GPS does not work in deep underwater environment. Even if the tactical inertial sensor can provide very detail measurement during long operation time, it is not suitable to use the tactical inertial sensor for small size and low cost UUV because the tactical inertial sensor is expensive and large. One alternative to INS is attitude heading reference system (AHRS) with the micro-machined electro mechanical system (MEMS) inertial sensor because of MEMS inertial sensor's small size and low power requirement. A cost effective and small size attitude heading reference system (AHRS) which incorporates measurements from 3-axis micro-machined electro mechanical system (MEMS) gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for UUV. The AHRS based MEMS overcome many problems that have inhibited the adoption of inertial system for small UUV such as cost, size and power consumption. Several evaluation experiments were carried out for the validation of the developed AHRS's function and these experiments results are presented. Experiments results prove the fact that the developed MEMS AHRS satisfied the required specification.

• 제어로봇시스템학회논문지
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• 제22권7호
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• pp.562-569
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• 2016

This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

• 전기학회논문지
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• 제65권1호
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• pp.135-141
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• 2016

Recently, the needs for the development and application of marine robots are increasing as marine accidents occur frequently. However, it is very difficult to acquire the information by utilizing marine robots in the marine environment. Therefore, the needs for the researches of sensor networks which are composed of underwater, surface and aerial robots are increasing in order to acquire the information effectively as the information from heterogeneous robots has less limitation in terms of coverage and connectivity. Although various researches of the sensor network which is based on marine robots have been executed, all of the underwater, surface and aerial robots have not yet been considered in the sensor network. To solve this problem, a collaborative control method based on the acoustic information and image by the sonars of the underwater robot, the acoustic information by the sonar of the surface robot and the optical image by the camera of the static-floating aerial robot is proposed. To verify the performance of the proposed method, the collaborative control of a MUR(Micro Underwater Robot) with an OAS(Obstacle Avoidance Sonar) and a SSS(Side Scan Sonar), a MSR(Micro Surface Robot) with an OAS and a BMAR(Balloon-based Micro Aerial Robot) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.

• International Journal of Ocean System Engineering
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• 제1권2호
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• pp.102-109
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• 2011

This paper describes the implementation of a precise underwater navigation solution using a multiple sensor fusion technique based on USBL, GPS, DVL and AHRS measurements for the operation of a remotely operated mine disposal vehicle (MDV). The estimation of accurate 6DOF positions and attitudes is the key factor in executing dangerous and complicated missions. To implement the precise underwater navigation, two strategies are chosen in this paper. Firstly, the sensor frame alignment to the body frame is conducted to enhance the performance of a standalone dead-reckoning algorithm. Secondly, absolute position data measured by USBL is fused to prevent cumulative integration error. The heading alignment error is identified by comparing the measured absolute positions with the DR algorithm results. The performance of the developed approach is evaluated with the experimental data acquired by MDV in the South-sea trial.

• 한국군사과학기술학회지
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• 제3권1호
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• pp.85-91
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• 2000

Underwater sensor accuracy test which measures the detection range and bearing accuracies of sonar simulates sonar transmitting ping and underwater radiating noise of target vessels. In this test, because the position of sonar target is the reference position of test, the sonar target position should be precisely estimated. Hence, this paper suggests to apply USBL algorithm which adopts cross phase spectrum of received sensor signals, and presents its performance by range and bearing estimation simulations. As a result of simulations, suggested algorithm shows good accuracy for underwater sensor accuracy test near 5㏈ SNR.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.175-175
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• 2000

In this Paper we propose a navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with biases and measurement noise, are investigated with theoretically data from KRISO's AUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system comment)'used aboard underwater vehicle.

• 제어로봇시스템학회논문지
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• 제21권4호
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.