• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.229-234
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• 1998

We study on a terrain contour matching algorithm using Radial Basis Functions(RBFs) for aided inertial navigation system for position fixing aircraft, cruise missiles or re-entry vehicles. The parameter optimization technique is used for updating the parameters describing the characteristics of an area with modified Gaussian least square differential correction algorithm and the step size limitation filter according to the amount of updates. We have applied the algorithm for matching a sampled area with a target area supposed that the area data are available from Radar Terrain Sensor(RTS) and Reference Altitude Sensor(RAS)

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.291-297
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• 2000

This paper presents an attitude determination algorithm for the local level strapdown inertial navigation where the body the earth and the transport rate can be calculated separately using a DCM computation scheme, Also presented is a velocity determination algorithm taking into account the attitude variation caused by he change of the navigation frame. The proposed algorithm are implemented using three samples of the velocity and the angle within the integration interval.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1144-1148
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• 1996

This paper presents WMR modelling and path tracking algorithm using Inertial Navigation System. The error models of gyroscope and accelerometers in INS are derived by Gauss-Newton method which is nonlinear regression model. Then, to test availability of error model, we pursue the fitness diagnosis about probability characteristic for real data and estimated data. Performance of inertial sensor with error model and Kalman filter is pursued by comparing with one without them. The computer simulation shows that position error remarkably decrease when error compensation is applied.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2188-2191
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• 2005

We consider a fault detection and isolation problem for inertial navigation systems which use redundant inertial sensors. We propose a FDI method using average of multiple parity vectors which reduce false alarm and wrong isolation, and improve correct isolation. We suggest the number of redundant sensors required to isolate simultaneous faults. The performance of the proposed FDI algorithm is analyzed by Monte-Carlo simulation.

• Nonlinear Functional Analysis and Applications
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• v.26 no.5
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• pp.995-1009
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• 2021

Many iterative algorithms like that Picard, Mann, Ishikawa and S-iteration are very useful to elucidate the fixed point problems of a nonlinear operators in various topological spaces. The recent trend for elucidate the fixed point via inertial iterative algorithm, in which next iterative depends on more than one previous terms. The purpose of the paper is to establish convergence theorems of new inertial Picard normal S-iteration algorithm for nonexpansive mapping in Hilbert spaces. The comparison of convergence of InerNSP and InerPNSP is done with InerSP (introduced by Phon-on et al. [25]) and MSP (introduced by Suparatulatorn et al. [27]) via numerical example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1746-1754
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• 2016

In this paper, we provide a development and evaluation method for an archery posture analyzing system, using an inertial sensor. The system was developed using LabVIEW2014 by National Instruments and evaluated using the DTW algorithm. To convert the voltage value of the inertial sensor into a physical value, a coordinate transformation matrix bias was applied. To evaluate the similarity of movement in archery shooting, the DTW distance was calculated and similarity was confirmed based on simple mechanical movement, the same person's shooting movement, shooting movement with another person, and the noise signal. The average similarity comparison results were as follows: simple mechanical movement was 17.05%, the same person's shooting movement was 26.48%, shooting movement with another person was 62.8%, and the noise signal was 328.5%; a smaller value indicates a higher level of similarity. We confirmed the possibility of analyzing the archery posture using 3-axis acceleration of the inertial sensor. We inferred that the proposed method might be important means for assessing shooting skills, evaluation of archer's progress, and finding talented archers in advance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.26-26
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• 2000

We study on the velocity matching algorithm for transfer alignment of inertial navigation system(INS) using robust H$_2$ filter. We suggest an uncertainty model for INS and apply the suggested discrete robust H$_2$ filter to the uncertainty model compared with kalman filter, the discrete robust H$_2$ filter is shown by simulation to have good performance of alignment time and accuracy.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.95-101
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• 2020

We studied the Implementation and design of inertial sensor that enables to improve performance by reduce the noise of rotor which Angle of inclination. Analyze model equation including motion equation and error, signal processing filter algorithm on high frequency bandwidth with eliminates error using estimation of error coefficient method is was designed and the prototype inertial sensor showed the pick off noise up to 0.2 mV and bias error performance of about 0.06 deg/hr by the experiments. Accordingly, we confirmed that the design of inertial sensor was valid for high rotation.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.245-250
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• 2019

Inertial navigation system has navigation errors because of the error of inertial measurement unit (IMU) and misalignment over time. In order to solve this problem, aided navigation system is performed using global navigation satellite system (GNSS), speedometer, etc. The inertial navigation system equipped with underwater vehicle mainly uses speedometer and performed aided navigation because satellite signals do not pass through underwater. There are DVL, EM-Log, and RPM in the speedometer, and the sensors are applied according to the system environment. This paper describes velocity aided navigation using RPM of inertial navigation system operating in high speed and deep water environment. In addition, we proposes an algorithm to compensate the limit of RPM with straight direction and the current velocity error. There are results of monte-calo simulation to prove performance of the proposed algorithm.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.16-23
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• 2020

This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.