• Journal of Ocean Engineering and Technology
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• v.19 no.5 s.66
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• pp.71-77
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• 2005

This paper presents an integrated underwater navigational algorithm for unmanned underwater vehicles, using additional two-range transducers. This paper proposes a measurement model, using two range measurements, to improve the performance of an IMU-DVL (inertial measurement unit - Doppler velocity log) navigation system for long-time operation of underwater vehicles, excluding DVL measurement. Extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation when the external measurements are available. Simulation was conducted with the 6-d.o.f nonlinear numerical model of an AUV in lawn-mowing survey mode, at current flaw, where the velocity information is unavailable. Simulations illustrate the effectiveness of the integrated navigation system, assisted by the additional range measurements without DVL sensing.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.107-112
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• 2016

Most of the indoor positioning algorithms based on magnetic data mainly focus on reducing the accumulated error of the odometry data, such as signals produced by the inertial sensors. However, in most cases such as positioning by using smartphones in the indoor environment, those approaches seem unfeasible due to the absence of the inertial sensors. Thus, in this paper, we try to study a positioning algorithm exclusively based on the magnetic data. We refer to some thinking from the steps of Particle Filter and conduct an experiment to verify the application of the new algorithm. Besides, we use the variance of the result of the previous step to decrease the area to be matched in the next step, intending to improve the accuracy of the results. The result of the experiment shows that the new algorithm has a high probability to match with accuracy less than 2 meters in a 24 meters by 2.6 meters corridor.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.314-320
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• 2016

Inertial navigation system (INS) has used aided systems and sensors to compensate navigation error. Global navigation satellite system (GNSS), velocity measurement sensor (VMS), and radar are commonly used to aid INS. Land navigation system (LNS) also mainly uses VMS when GNSS cannot be used such as at tunnel or on jammed scenario. A straight drive is required when VMS-aided navigation is used, because there is only speed of straight direction whereas no crossways and vertical directions. In local environment, even an expressway has lack of straight drive which is constraint of VMS-aided navigation algorithm. This paper proposes an enhanced VMS-aided navigation algorithm for LNS with indirect drive by restricting filter update condition. Also, there is a result of vehicle test to prove performance of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.314-320
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• 2012

This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.200-206
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• 2005

In this paper, a redundancy management system for aircraft is studied, and FDI (Fault Detection and Isolation) algorithm of inertial sensor system is proposed. UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional FDI method cannot isolate multiple faults in a triple redundancy system. In this paper, hardware based FDI technique is proposed, which combines a parity equation approach with the wavelet based technique, which is a model-free FDI method. To verify the effectiveness of the proposed FDI method, numerical simulations are performed.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.343-345
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• 2007

This paper proposes an inertial navigation system(INS) with which a biped robot can determine his position, velocity, posture, etc. The proposed system provides the information of robots independently without using any outer signals. The defect of the algorithm is the en'or accumulation as the robot increases the mobile range. However, in this application the problem is not so critical because the working space is small and operation period of the robots is relatively short. With the proposed INS system biped robots obtain enhanced intelligence to execute their tasks. The structure and theoretical backgrounds are utilized to design the INS system. The method for application of INS system to biped robots has been illustrated.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.626-637
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• 2014

On ship, especially on large ship, the flexure deformation between Master (M)/Slave (S) Inertial Navigation System (INS) is a key factor which determines the accuracy of the integrated system of M/S INS. In engineering this flexure deformation will be increased with the added ship size. In the M/S INS integrated system, the attitude error between MINS and SINS cannot really reflect the misalignment angle change of SINS due to the flexure deformation. At the same time, the flexure deformation will bring the change of the lever arm size, which further induces the uncertainty of lever arm velocity, resulting in the velocity matching error. To solve this problem, a $H_{\infty}$ algorithm is proposed, in which the attitude and velocity matching error caused by deformation is considered as measurement noise with limited energy, and measurement noise will be restrained by the robustness of $H_{\infty}$ filter. Based on the classical "attitude plus velocity" matching method, the progress of M/S INS information fusion is simulated and compared by using three kinds of schemes, which are known and unknown flexure deformation with standard Kalman filter, and unknown flexure deformation with $H_{\infty}$ filter, respectively. Simulation results indicate that $H_{\infty}$ filter can effectively improve the accuracy of information fusion when flexure deformation is unknown but non-ignorable.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.673-683
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• 2010

This study investigates Terrain Aided Inertial Navigation(TAIN) which consists of Inertial Navigation System (INS) with the optical sensor for precise planetary landing. Image processing is conducted to extract the feature points between measured terrain data and on-board implemented terrain information. The navigation algorithm with Iterated Extended Kalman Filter(IEKF) can compensate for the navigation error, and provide precise navigation information compared to single INS. Simulation results are used to demonstrate the feasibility of integration to accomplish precise planetary landing. The proposed navigation approach can be implemented to the whole system coupled with guidance and control laws.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.9
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• pp.617-625
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• 2022

This study investigates the use of movable calibration target for gyroscopic and accelerometer bias compensation of inertial measurement units for firing lane alignment. Calibration source is detected with the help of vision sensor and its information in fused with other sensors on launcher for error correction. An algorithm is proposed and tested in simulation. It has been shown that it is possible to compensate sensor biases in firing launcher in few seconds by accurately estimating the location of calibration target in inertial frame of reference.

• Smart Structures and Systems
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• v.31 no.6
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• pp.561-571
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• 2023

Ensuring the safety of a structure necessitates that repairs are carried out based on accurate inspections and records of damage information. Traditional methods of recording damage rely on individual paper-based documents, making it challenging for inspectors to accurately record damage locations and track chronological changes. Recent research has suggested the adoption of building information modeling (BIM) to record detailed damage information; however, localizing damages on a BIM model can be time-consuming. To overcome this limitation, this study proposes a method to automatically localize damages on a BIM model in real-time, utilizing consecutive images and measurements from an inertial measurement unit in close proximity to damages. The proposed method employs a visual-inertial odometry algorithm to estimate the camera pose, detect damages, and compute the damage location in the coordinate of a prebuilt BIM model. The feasibility and effectiveness of the proposed method were validated through an experiment conducted on a campus building. Results revealed that the proposed method successfully localized damages on the BIM model in real-time, with a root mean square error of 6.6 cm.