• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.426-432
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• 2012

The positions of vessels in JTIDS where each vessel broadcasts its position, can be found using the relative navigation method. Besides positioning, the relative navigation could be adopted for identification friend or foe, tracking targets, monitoring battle field and etc. In this paper, we have explained the fundamental operation and technical structure for the relative navigation and implemented the simulation platform to evaluate the basic function and performance of the system in arbitrary environment. Using platform, the availability of relative navigation within the group network and the characteristic of the algorithm for position prediction was verified. Based on the simulation result, it was verified that EKF based navigation algorithm could produce great initial error and need quite convergence time. To improve the performance, we proposed a new navigation algorithm which uses the minimum norm estimation algorithm until the EKF converges. The simulation results reveal the relative navigation can be effectively used in the formation flight and collision avoidance system.

• Journal of Advanced Navigation Technology
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• v.24 no.1
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• pp.16-27
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• 2020

This paper investigates the applicability of optical flow information for unmanned aerial vehicle (UAV) navigation under environments where global navigation satellite system (GNSS) is unavailable. Since the optical flow information is one of important measurements to estimate horizontal velocity and position, accuracy of the optical flow information must be guaranteed. So a navigation algorithm, which can estimate and cancel biases that the optical flow information may have, is suggested to improve the estimation performance. In order to apply and verify the proposed algorithm, an integrated simulation environment is built by designing a guidance, navigation, and control (GNC) system. Numerical simulations are implemented to analyze the navigation performance using this environment.

• Smart Structures and Systems
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• v.6 no.9
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• pp.1057-1077
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• 2010

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

• International Area Studies Review
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• v.15 no.3
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• pp.55-76
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• 2011

In this paper, we estimate a model that incorporates key features of business cycles, co-movement among economic variables and switching between regimes of expansion and recession, to aggregate quarterly data for the NAFTA region. Two common factors reflecting the permanent and transitory components of the business cycle in the region, along with the turning points from one regime to the other, were extracted from the data by using the Kalman filter and maximum likelihood estimation approach of Kim (1994). Estimation results confirm that a typical aspect of business cycles are also observed (i.e., recessions are steeper and shorter than recoveries) in the region, and that both co-movement and that regime switching are found to be important features of the business cycle. The two common factors produce sensible representations of the trend and cycle, and the estimated turning points are in line with independently determined chronologies. It also turns out that the degree of synchronization between the NAFTA region and Korea, has significantly increased since the entry into force of the NAFTA.

• International Area Studies Review
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• v.21 no.4
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• pp.159-172
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• 2017

In a typical trend-cycle decomposition of GDP, the trend component is usually assumed to follow a random walk process. This paper considers an ARIMA trend and assesses the validity of the ARIMA trend model. I construct univariate and bivariate unobserved-components(UC) models, allowing the ARIMA trend. Estimation results using U.S. data are favorable to the ARIMA trend models. I, also, compare the forecasting performance of the UC models. Dynamic pseudo-out-of-sample forecasting exercises are implemented with recursive estimations. I find that the bivariate model outperforms the univariate model, the smoothed estimates of trend and cycle components deliver smaller forecasting errors compared to the filtered estimates, and, most importantly, allowing for the ARIMA trend can lead to statistically significant gains in forecast accuracy, providing support for the ARIMA trend model. It is worthy of notice that trend shocks play the main source of the output fluctuation if the ARIMA trend is allowed in the UC model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.2
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• pp.307-316
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• 1994

The rainfall forecasting model of the short term is improved at the point where meterological data is not gaged. In this study, the adopted model is based on the assumptions for simulation model of rainfall process, meteorological homogeneousness, prediction and estimation of meteorological data. A Kalman Filter technique is used for rainfall forecasting. In the existing models, the equation of the model is non-linear type with regard to rainfall rate, because hydrometer size distribution (HSD) depends on rainfall intensity. The equation is linearized about rainfall rate as HSD is formulated by the function of the water storage in the cloud. And meteorological input variables are predicted by emprical model. It is applied to the storm events over Taech'ong Dam area. The results show that root mean square error between the forecasted and the observed rainfall intensity is varing from 0.3 to 1.01 mm/hr. It is suggested that the assumptions of this study be reasonable and our model is useful for the short term rainfall forecasting at the ungaged point of the meteorological data.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.4
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• pp.174-180
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• 2006

The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional braking control systems. In order to achieve the superior braking performance through the wheel slip control, real-time information such as the tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance, stability enhancement, etc. In this paper, a wheel slip control system is developed for maintaining the vehicle stability based on the braking monitor, wheel slip controller and optimal target slip assignment algorithm. The braking monitor estimates the tire braking force, lateral tire force and brake disk-pad friction coefficient utilizing the extended Kalman filter. The wheel slip controller is designed based on the sliding mode control method. The target slip assignment algorithm is proposed to maintain the vehicle stability based on the direct yaw moment controller and fuzzy logic. The performance of the proposed wheel slip control system is verified in simulations and demonstrates the effectiveness of the wheel slip control in various road conditions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.221-228
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• 2014

In this paper, the operational concept and the navigation algorithms for the gliding guided artillery munition are studied. The gliding guided artillery munition has wings for gliding; therefore spin of the munition should be eliminated. The previous navigation algorithms assumed a spinning munition with constant angular velocity; hence, they cannot be applied for the gliding munition. Moreover, lateral stability becomes worse due to decrease of angular momentum. Therefore, side force should be controlled to improve the stability, and the munition should maneuver, then the previous navigation algorithms for typical fixed-wing aircraft cannot be applied. In this paper, we apply the previous navigation algorithms for the spinning munition. Spin is eliminated and wings are deployed based on the estimation results, and the advanced navigation algorithm for the non-spinning munition is introduced.