Navigation System for a Deep-sea ROV Fusing USBL, DVL, and Heading Measurements

Lee, Pan-Mook; Shim, Hyun Woo; Baek, Hyuk; Kim, Banghyun; Park, Jin-Yeong; Jun, Bong-Huan; Yoo, Seong-Yeon

doi:10.26748/ksoe.2017.08.31.4.315

Cited by 7 publications

(9 citation statements)

References 6 publications

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“…In this condition, the USBL Fig. 2 Angular measurement errors of the USBL acoustic positioning system system has been successfully applied to aiding a navigation system as an auxiliary sensor in a previous study (Lee et al, 2017). If an AUV is performing a long-range exploration in an ice sheet or operating in a shallow water, the error in the radial direction will be constant regardless of the range as well.…”

Section: Position Measurements Of Usbl In the Horizontal Planementioning

confidence: 98%

“…In this study, a dead-reckoning navigation method was applied to estimate the position. The simple equation of motion was established using only the speed, bearing angle, and position information of the AUV (Lee et al, 2017). If the AUV operates at a constant speed and the accelerations of the vehicle can be assumed decoupled normal noises in each direction, the equation of motion can be expressed as follows:…”

Section: Usbl-aided Navigation System Of Auvs In Shallow Watermentioning

confidence: 99%

“…In addition, the USBL can measure the position of the underwater object within a certain error bound regardless of the elapsed time. It is also employed as an auxiliary sensor for aiding the navigation systems of underwater vehicles composed of inertial sensors (Vasilijevic et al, 2012;Lee et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Underwater Navigation of AUVs Using Uncorrelated Measurement Error Model of USBL

Lee¹,

Park²,

Baek³

et al. 2022

J. Ocean Eng. Technol.

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This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x-and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.

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Section: Position Measurements Of Usbl In the Horizontal Planementioning

confidence: 98%

Section: Usbl-aided Navigation System Of Auvs In Shallow Watermentioning

confidence: 99%

See 1 more Smart Citation

Underwater Navigation of AUVs Using Uncorrelated Measurement Error Model of USBL

Lee¹,

Park²,

Baek³

et al. 2022

J. Ocean Eng. Technol.

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“…The state variable estimated by the Kalman filter is set as the posture of the quaternion, and the measured value model H can be expressed as equation (12):…”

Section: Design Of Inertial Navigation Systemmentioning

confidence: 99%

“…10,11 Furthermore, another study has been conducted on developing a navigation system by fusing navigation sensors and preparing against blackouts by identifying outliers. 12 In this study, a navigation algorithm that integrates an inertial measurement unit (IMU), a magnetic compass, and a global positioning system (GPS) is designed. Moreover, the GPS was designed to reduce the position error by applying a technique to remove outliers.…”

Section: Introductionmentioning

confidence: 99%

Outlier rejection for reducing position error in navigation system based on multi sensors

Jeong

Choi

et al. 2022

Measurement and Control

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A navigation system is critical for the operation of autonomous vehicles. Various sensors must be used to build navigation systems. To fuse multiple sensors, a highly advanced filter algorithm is required. Navigation systems have difficulties in signal-degraded scenarios, where the navigation solution can be degraded by errors such as multipath and obscured signals. This paper proposes a navigation system using a technique to reject the outliers measured by sensors. The navigation system was designed to include sensor modeling, navigation filters, and outlier rejection. The sensors used in the navigation system are the accelerometer, gyroscope, magnetometer, and global positioning system. Before the experiment, a navigation simulation was performed to evaluate the results and validate the proposed navigation algorithm. The results of the experiment verified that the navigation system, including outlier rejection, had less positional error than that of the general navigation system.

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Operational Improvement of Hemire ROV for Deep-sea Survey and Application to Exploration of Ferromanganese Crusts of Western Pacific Seamount

Baek¹,

Park²,

Shim³

et al. 2018

J. Ocean Eng. Technol.

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This paper presents the results of an exploration of the ferromanganese crusts of Western Pacific Seamount registered by the Korean government. This area has been surveyed with a deep-sea camera and crust samples have been acquired by deep-sea dredging since 2013. On October 18-19, 2017, a united research team from KIOST and KRISO explored two blocks, OSM11 and OSM07, on the seamount using Hemire ROV. A precise survey was conducted on the ferromanganese crusts and sediments covering the slope/top of OSM11 and the middle flat area of OSM07. Rock samples were collected with precise positioning, and HD videos were recorded for 7 hours. This paper discusses the technical issues of this exploration in terms of (1) how to deal with an emergency situation during an electric power blackout, (2) the improvement of the thruster power by adding cooling plugs to the housings of the thruster amplifiers, (3) the relative motion of the depressor by changing the fixing method of the cable terminator, which affects the service life of the cable, (4) a sampling technique for the steep slope of the seamount, (5) integrated navigation under a USBL blackout, and (6) a 3-dimensional image mosaic for visualizing the distribution state of the crusts.

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Navigation System for a Deep-sea ROV Fusing USBL, DVL, and Heading Measurements

Cited by 7 publications

References 6 publications

Underwater Navigation of AUVs Using Uncorrelated Measurement Error Model of USBL

Underwater Navigation of AUVs Using Uncorrelated Measurement Error Model of USBL

Outlier rejection for reducing position error in navigation system based on multi sensors

Operational Improvement of Hemire ROV for Deep-sea Survey and Application to Exploration of Ferromanganese Crusts of Western Pacific Seamount

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