• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.27-31
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• 2003

Underwater acoustic navigation systems are classified into three systems: ultra-short baseline (USBL), short baseline (SBL), and long baseline (LBL). Because the USBL system estimates the angle of a submersible, the estimation error becomes large if the submersible is far from the USBL transducer array mounted under a support vessel. SBL and LBL systems estimate submersible's location more accurately because they have wider distribution of measuring sensors. Especially LBL systems are widely used as a navigation system for deep ocean applications. Although it is most accurate system it still has estimation errors because of noise, measurement error, refraction and multi-path of acoustic signal, or wrong information of the distributed transponders. In this paper the estimation error of the LBL system are analyzed from a point of sensitivity. It is assumed that the error exists only in the distance between a submersible and the transponders. For this purpose sensitivity of the estimated position with respect to relative distances between them is analyzed. The result says that estimation error is small if the submersible is close to transponders but not near the ocean bottom.

• Journal of Ship and Ocean Technology
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• v.11 no.1
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• pp.36-46
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• 2007

The maintenance of a ship is essential for safe navigation and hence regular surveys are prescribed according to the rule of classification societies. A hull inspection is generally performed by professional divers, but it takes a long time and the efficiency is low in terms of time and cost. In this research, a ROV(Remotely Operated Vehicle) named as SNU-ROV(Seoul National University-ROV) is developed to replace the conventional inspection method. In this system, the ROV is intended to be used for inspecting ship and harbor because harbor inspection is merging as a safety measure against any possible terror actions. In order to increase the efficiency of inspection, the ROV must be able to measure the exact position of damages. SNU-ROV has a positioning system based on LBL(Long Base Line). In shallow water such as harbor, however, LBL has bad DOP(Dilution of Precision) in the depth direction due to the limited depth. Thus LBL only can not locate the exact depth position. To solve the DOP problem, a pressure sensor is introduced to LBL and a complementary filter is attached by using indirect feedback Kalman filter. Thus developed positioning system is verified by simulation and experiment in towing tank.

• Ocean and Polar Research
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• v.27 no.3
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• pp.335-339
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• 2005

The underwater positioning system is important in interpreting data that are acquired from towing vehicles such as the deep-sea camera (DSC) system. Currently, several acoustic positioning systems such as long baseline (LBL), short baseline (SBL), and ultra short baseline (USBL), are used for underwater positioning. The accurate position of DSC, however, could not be determined in a R/V Onnuri unequipped with any of these underwater positioning systems. As an alternative, the DSC position was estimated based on the topography of towing track and cable length in the cruises before 1999. The great uncertainties, however, were found in the areas of flat bottom topography. In the 2003 and 2004 cruises these uncertainties were reduced by calculating the position of DSC with the cable length and seafloor depth below the vessel. The Japanese cruises for Mn-nodule used a similar estimation method for the DSC positioning system with a CTD sensor. Although the latter can provide better information for the position of DSC, the USBL underwater positioning system is strongly recommended for establishing better positioning of DSC and other towing devices.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.11a
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• pp.204-209
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• 2004

It is well known fact that acoustic positioning systems are absolutely needed for various underwater operations. According to the distances between their sensors they are classified into three parts: long baseline(LBL), short baseline(SBL), and ultra-short baseline(USBL). Among them the USBL system is widely used because of its simplicity, although it is the most inaccurate. Recently, in order to increase the positioning accuracy, various USBL systems using broadband signal such as MFSK(Multiple Frequency Shift Keying) are produced. However, their positioning accuracy is still limited by background noise and reflected waves. Therefore, there is difficulty in applying the USBL system using MFSK signal in a shallow water with noisy conditions. In order to examine the effect of the noise and wave reflections this paper analyze position errors for various conditions using numerical simulations. The simulation results say that tile SNR must be greater than 20dB and errors in the vertical direction are slightly increased by wave reflections by upper and lower boundaries.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.89-94
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• 2011

Underwater localization is a crucial capability for reliable operation of various types of underwater vehicles including submarines and underwater robots. However, sea water is almost impermeable to high-frequency electromagnetic waves, and thus absolute position fixes from Global Positioning System (GPS) are not available in the water. The use of acoustic telemetry systems such as Long Baseline (LBL) is a practical option for underwater localization. However, this telemetry network system needs to be pre-deployed and its availability cannot always be assumed. This study focuses on demonstrating the validity of terrain-based localization techniques in a GPS-denied underwater environment. Since terrain-based localization leads to a nonlinear estimation problem, nonlinear filtering methods are required to be employed. The extended Kalman filter (EKF) which is a widely used nonlinear filtering algorithm often shows limited performance under large initial uncertainty. The feasibility of using a particle filter is investigated, which can improve the performance and reliability of the terrain-based localization.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.702-708
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• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.