• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1230-1242
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• 2007

This paper describes an IIR/FIR fusion filter for a nonlinear system, and analyzes the stability of the fusion filter. The fusion filter is applied to INS/GPS integrated system, and the performance is verified by simulation and experiment. In the fusion filter, an IIR-type filter (SPKF) and FIR-type filter (MRHKF filter) are processed independently, then the two filters are merged using the mixing probability calculated using the residuals and residual covariance information of the two filters. The merits of the SPKF and the MRHKF filter are embossed and the demerits of the filters are diminished via the filter fusion. Consequently, the proposed fusion filter has robustness against to model uncertainty, temporary disturbing noise, large initial estimation error, etc. The stability of the fusion filter is verified by showing the closeness of the states of the two sub filters in the mixing/redistribution process and the upper bound of the error covariance matrices. This fusion filter is applied into INS/GPS integrated system, and important factors for filter processing are presented. The performance of the INS/GPS integrated system designed using the fusion filter is verified by simulation under various error environments and is confirmed by experiment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1243-1251
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• 2007

In this paper a study on the simplified observability analysis of GPS/INS is introduced. Errors for the position, velocity, attitude, gyro and accelerometer biases, and lever arm between GPS antenna and inertial sensors are considered in the observablity analysis. From the error dynamics model in which relatively small terms are neglected, simple observability conditions are obtained such that the observability of GPS/INS is determined by the test on the attutude, gyro bias, and lever arm. Unobservable errors for the position, velocity, and accelerometer bias are determined by those for the attitude, gyro bias, and lever arm. The simplified observability conditions are applied to a constant speed horizontal motion. It is shown that there are seven unobservable modes for the motion including the vertical component of gyro bias. The analytic observability analysis results are confirmed with a covariance simulation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.47-52
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• 2002

There are many factors in machine tool error. These are thermal deformation, geometric error, machine's part assembly error, error caused by tool bending. Among them thermal error is 70% of total error of machine tool . Prediction of thermal error is very difficult. because of nonlinear tendency of machine tool deformation. In this study, we tried thermal error prediction by using multi regression analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2751-2757
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• 2015

To obtain the system requirement specification in the beginning of the precision guidance and control system development, the effectiveness and reliability analysis for the system are necessary. The main purpose of this research is to obtain the system requirement specification by carrying out the effectiveness analysis using the modeling and simulation(M&S) scheme. M&S model is constructed using 6-DOF dynamic model, environment model, guidanc -navigation & control model. Assume that the navigation sensor is consist of inertial navigation sensor(INS) and doppler velocity log(DVL), and the speed and direction of current is environment parameter. The effectiveness analysis is carried out using circular error probability(CEP) and variance analyze scheme. Also, the effectiveness analysis is utilized for cost-performance analysis considering the cost of commercial INS and DVL sensor. This paper shows the high-level INS and the low-level DVL configure a high price-performance integrated navigation system.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.51-64
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• 2009

A location tracking sensor such as GPS, INS, Radar, and optical equipments is used in tracking Maneuvering Targets with a multi-sensor, and such systems are used to track, detect, and control UAV, guided missile, and spaceship. Until now, Most of the studies related to tracking Maneuvering Targets are on fusing multiple Radars, or adding a supplementary sensor to INS and GPS. However, A study is required to change the degree of application in fusions since the system property and error property are different from sensors. In this paper, we perform the error analysis of the sensor properties by adding a ground radar to GPS and INS for improving the tracking performance by multi-sensor fusion, and suggest the tracking algorithm that improves the precision and stability by changing the sensor probability of each sensor according to the error. For evaluation, we extract the altitude values in a simulation for the trajectory of UAV and apply the suggested algorithm to carry out the performance analysis. In this study, we change the weight of the evaluated values according to the degree of error between the navigation information of each sensor to improve the precision of navigation information, and made it possible to have a strong tracking which is not affected by external purposed environmental change and disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.64.1-64
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• 2001

Errors in inertial navigation system(INS) can be divided into two major groups which are system related errors and modeling errors due to approximation and linearization. Measurement noise, calibration, and alignment errors make up the first group, whereas the uncertainties in the gravity vector fall in the second category and are important error source for high quality INS, especially during high altitude and and/or long time missions, when the gravity errors tent to build up. The quality of a medium to high accuracy INS depends on the knowledge of the local gravity field. In this paper, the feasibility of improving airborns INS by use of more accurate gravity model is studied. To make consistent comparisons, WGS-84 parameters are used and ...

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.619-632
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• 2023

Purpose: The main function of INS (Inertial Navigation System) is to measure the position of an armed vehicle and its performance is confirmed through the positioning accuracy test of Korean Defense Standards (KDS). The current standards, however, do not provide clear test methods and the conditions for performing positioning accuracy tests. Accordingly, the purpose of this study is to develop a new method for positioning accuracy test which would be effective. Methods: In this study, a new INS positioning accuracy test method is suggested based on the analysis of test data collected through a statistical experiment known as central composite design. For the positioning accuracy experiment of K105A1, a self-propelled artillery, two factors of driving velocity and driving distance are considered. Results: Based on the analysis of experimental data, a regression model for the positioning error is fitted and the positioning accuracy test of INS is so developed to maximize the positioning error. The standard proximity rate is used as an additional test criterion to evaluate the performance level of INS. Conclusion: The proposed new positioning accuracy test for INS has the advantage of finding the nonconforming items effectively. It is also expected to be utilized for the other similar INS positioning accuracy tests.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.183-189
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• 2011

An alignment algorithm for strapdown inertial navigation systems is proposed, in which the psi angle error model is utilized. The proposed alignment algorithm is derived from the Psi angle error model which has been widely used in real-time navigation systems. The equation for expecting steady state alignment error is also derived. The proposed algorithm was verified through real-time experiments. Experimental results show that the proposed algorithm can be used in the inertial navigation system and GNSS/INS integrated navigation system to get an initial attitude of the vehicle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.693-699
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• 2006

Digital airborne image must be precisely orthorectified to become geographical information. For orthorectification of airborne images, GPS/INS (Global Positioning System/Inertial Navigation System) and LIDAR (LIght Detection And Ranging) elevation data were employed. In this study, 635 frame airborne images were produced and LIDAR data were converted to raster image for applying to image orthorectification. To derive images with constant brightness, flat field correction was applied to images. The airborne images were geometrically corrected by calculating internal orientation and external orientation using GPS/INS data and then orthorectified using LIDAR digital elevation model image. The precision of orthorectified images was validated by collecting 50 ground control points from arbitrary five images and LIDAR intensity image. As validation result, RMSE (Root Mean Square Error) was 0.387 as almost same as only two times of pixel spatial resolution. It is possible that this automatic orthorectification method of airborne image with higher precision is applied to airborne image industry.