Kihun Kim

Simulation of an Inertial Acoustic Navigation System With Range Aiding for an Autonomous Underwater Vehicle

This paper presents an integrated navigation system for underwater vehicles to improve the performance of a conventional inertial acoustic navigation system by introducing range measurement. The integrated navigation system is based on a strapdown inertial navigation system (SDINS) accompanying range sensor, Doppler velocity log (DVL), magnetic compass, and depth sensor. Two measurement models of the range sensor are derived and augmented to the inertial acoustic navigation system, respectively. A multirate extended Kalman filter (EKF) is adopted to propagate the error covariance with the inertial sensors, where the filter updates the measurement errors and the error covariance and corrects the system states when the external measurements are available. This paper demonstrates the improvement on the robustness and convergence of the integrated navigation system with range aiding (RA). This paper used experimental data obtained from a rotating arm test with a fish model to simulate the navigational performance. Strong points of the navigation system are the elimination of initial position errors and the robustness on the dropout of acoustic signals. The convergence speed and conditions of the initial error removal are examined with Monte Carlo simulation. In addition, numerical simulations are conducted with the six-degrees-of-freedom (6-DOF) equations of motion of an autonomous underwater vehicle (AUV) in a boustrophedon survey mode to illustrate the effectiveness of the integrated navigation system.

Estimation of hydrodynamic coefficients for an AUV using nonlinear observers

Hydrodynamic coefficients strongly affect the dynamic performance of an autonomous underwater vehicle. Although these coefficients are generally obtained experimentally such as through the planar-motion-mechanism (PMM) test, the measured values are not completely reliable because of experimental difficulties and errors involved. Another approach by which these coefficients can be obtained is the observer method, in which a model-based estimation algorithm predicts the coefficients. In this paper, the hydrodynamic coefficients are estimated using two nonlinear observers - a sliding mode observer and an extended Kalman filter. Their performances are evaluated by comparing the estimated coefficients obtained from the two observer methods with the values as determined from the PMM test. By using the estimated coefficients, a sliding mode controller is constructed for the diving and steering maneuver. It is demonstrated that the controller with the estimated values maintains the desired depth and path with sufficient accuracy.

The effect of the El Niño‐Southern Oscillation on U.S. regional and coastal sea level

Although much of the focus on future sea level rise concerns the long-term trend associated with anthropogenic warming, on shorter time scales, internal climate variability can contribute significantly to regional sea level. Such sea level variability should be taken into consideration when planning efforts to mitigate the effects of future sea level change. In this study, we quantify the contribution to regional sea level of the El Nino-Southern Oscillation (ENSO). Through cyclostationary empirical orthogonal function analysis (CSEOF) of the long reconstructed sea level data set and of a set of U.S. tide gauges, two global modes dominated by Pacific Ocean variability are identified and related to ENSO and, by extension, the Pacific Decadal Oscillation. By estimating the combined contribution of these two modes to regional sea level, we find that ENSO can contribute significantly on short time scales, with contributions of up to 20 cm along the west coast of the U.S. The CSEOF decomposition of the long tide gauge records around the U.S. highlights the influence of ENSO on the U.S. east coast. Tandem analyses of both the reconstructed and tide gauge records also examine the utility of the sea level reconstructions for near-coast studies.

Depth and heading control for autonomous underwater vehicle using estimated hydrodynamic coefficients

Depth and heading control of an AUV are considered for the predetermined depth and heading angle. The proposed control algorithm is based on a sliding mode control using estimated hydrodynamic coefficients. The hydrodynamic coefficients are estimated with the help of conventional nonlinear observer techniques such as sliding mode observer and extended Kalman filter. By using the estimated coefficients, a sliding mode controller is constructed for the combined diving and steering maneuver. The simulation results of the proposed control system are compared with those of control system with true coefficients. It is demonstrated that the proposed control system makes the system stable and maintains the desired depth and heading angle with sufficient accuracy.

Implementation and test of ISiMI100 AUV for a member of AUVs Fleet

This paper presents implementation and test of autonomous underwater vehicles(AUVs) for AUVs fleet. Recently, AUVs have become a main tool to survey underwater in scientific, and commercial applications because of the significant improvement of performance and low working costs. However, it is very time-consuming work to survey a wide area by an AUV. So the concept of AUVs fleet attracts much attention in the field of AUV technologies. Currently, Maritime and Ocean Engineering Research Institute (MOERI) is developing the technologies of AUVs fleet from 2006. The AUV fleet consists of an unmanned surface vehicle (USV) and three AUVs. This paper introduces the AUV ISiMI100 for a member of the AUVs fleet.

An ongoing shift in Pacific Ocean sea level

Based on the satellite altimeter data, sea level off the west coast of the United States has increased over the past 5 years, while sea level in the western tropical Pacific has declined. Understanding whether this is a short-term shift or the beginning of a longer-term change in sea level has important implications for coastal planning efforts in the coming decades. Here, we identify and quantify the recent shift in Pacific Ocean sea level, and also seek to describe the variability in a manner consistent with recent descriptions of El Nino-Southern Oscillation (ENSO) and particularly the Pacific Decadal Oscillation (PDO). More specifically, we extract two dominant modes of sea level variability, one related to the biennial oscillation associated with ENSO and the other representative of lower-frequency variability with a strong signal in the northern Pacific. We rely on cyclostationary empirical orthogonal function (CSEOF) analysis along with sea level reconstructions to describe these modes and provide historical context for the recent sea level changes observed in the Pacific. As a result, we find that a shift in sea level has occurred in the Pacific Ocean over the past few years that will likely persist in the coming years, leading to substantially higher sea level off the west coast of the United States and lower sea level in the western tropical Pacific.

Navigation and Control System of a Deep-sea Unmanned Underwater Vehicle 'HEMIRE'

This paper presents a hybrid underwater navigation and control system for positioning, guidance and control of a deep-sea unmanned underwater vehicle (UUV), HEMIRE. For precise navigation of the UUV, the hybrid navigation system is designed based on strap-down IMU (inertial measurement unit) accompanying with USBL (ultra-short base line), DVL (Doppler velocity log), range sonar, depth and heading sensors. Initial localization and position reference of the UUV are performed with the USBL when the vehicles are in stationary condition. This paper also presents the characteristics of the UUV and the system constitution of the surface control unit. HEMIRE is equipped with two hydraulic manipulators, ORION, which are remotely controlled at the surface vessel via fiber optic communication. An operator can control the manipulators with a workspace-controlled master arm as well as a parallel-type master arm. This paper describes the task-oriented control of the tele-operated robotic arms mounted on HEMIRE and its application to task-oriented joint configurations.

A comparative study of sea level reconstruction techniques using 20 years of satellite altimetry data

Sea level reconstructions extend spatially dense data sets, such as those from satellite altimetry, by decomposing the data set into basis functions and fitting those functions to in situ tide gauge measurements with a longer temporal record. We compare and evaluate two methods for reconstructing sea level through an idealized study. The compared sea level reconstruction methods differ in the technique for calculating basis functions, i.e., empirical orthogonal functions (EOFs) versus cyclostationary EOFs (CSEOFs). Reconstructions are created using Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) satellite altimetry data and synthetic tide gauges. Synthetic tide gauge records are simulated using historical distributions and real high-frequency signal to test reconstruction skill. The CSEOF reconstructions show high skill in reproducing variations in global mean sea level (GMSL) and ocean climate indices, and are affected less by both limited tide gauge distribution and added high-frequency tide gauge signal than EOF reconstructions. Typically, CSEOF reconstructions slightly underestimate sea level amplitudes while EOF reconstructions overestimate sea level amplitudes, in some cases, significantly. Both of these results are accentuated with decreasing quality of the synthetic tide gauge data set. Additionally, we investigate how the reconstructions differ when reconstructing with more of the variance retained in the basis functions. Increasing the variance explained by the basis functions from 70% to 90% reduces the efficacy of an EOF reconstruction to reproduce common ocean indices when noise is included in the tide gauge data sets. These results show that in the idealized comparative cases examined the CSEOF method of sea level reconstruction creates more robust reconstructions, especially when less than ideal tide gauge data are used.

Navigation and control for a test bed AUV-SNUUV I

This paper describes the design of underwater navigation and control system useful for towing tank experiments of a test bed autonomous underwater vehicle (AUV) named by SNUUV I (Seoul National University Underwater Vehicle I). A 6 DOF dynamic model for the SNUUV I is derived with hydrodynamic coefficients, which are estimated with the help of the Extended Kalman Filter (EKF) and a potential code. Based on a mathematical model, a nonlinear sliding mode controller is designed for diving and steering maneuvers of SNUUV I. A navigation algorithm is developed using three ranging sonars keeping the towing tank condition in mind. It is demonstrated numerically that the navigation system together with the controller guides the vehicle to follow the desired depth and path with sufficient accuracy.

Underwater precise navigation using multiple sensor fusion

This paper introduces the implementation of a precise underwater navigation solution using multi-sensor fusion technique, which is based on USBL, DGPS, DVL and AHRS measurements. To realize the accurate, precise and frequent update rate underwater navigation solution, three strategies are chosen. The first one is the heading angle calibration to enhance the performance of standalone dead-reckoning algorithm. The second one is introduction of effective outlier rejection algorithm. The third one is that absolute position is fused timely to prevent error accumulation of dead-reckoning, where the absolute position can be acquired from USBL or DGPS measurements considering predefined finite state machine. The performance of the developed algorithm is verified with experimental data of UUV(Unmanned underwater vehicle) at Sea with various operation scenario.