• Journal of KIISE:Databases
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• v.31 no.5
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• pp.479-491
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• 2004

Location information of mobile objects is applied to vehicle tracking, digital battlefields, location based services, and telematics. Their location coordinates are periodically measured and stored in the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the mobile object moving on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function, although the proposed location estimation function uses the small amount of information. The proposed method has an advantage that drops the cost of data storage space and communication for the management of location information of the mobile objects.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.53-62
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• 1994

This paper presents a new approach of analyzing errors resulting from nonideal general-purpose lighting environment when the Photometric Stereo Method (PSM) is applied to estimate the surface-orientation of a three-dimensional object. The approach introduces the explicit modeling of the lighting environment including a circular-disk type irradiance object plane and the direct simulation of the error distribution with the model. The light source is modeled as a point source that has a certain amount of beam angle, and the luminance distribution on the irradiance plane is modeled as a Gaussian function with different deviation values. A simulation algorithm is devised to estimate the light source orientation computing the average luminance intensities obtained from the irradiance object planes positioned in three different orientations. The effect of the nonideal lighting model is directly reflected in such simulation, because of the analogy between the PSM and the proposed algorithm. With an instrumental tool designed to provide arbitrary orientations of the object plane at the origin of the coordinate system, experiment can be performed in a systematic way for the error analysis and compensation. Simulations are performed to find out the error distribution by widely varying the light model and the orientation set of the object plane. The simulation results are compared with those of the experiment performed in the same way as the simulation. It is confirmed from the experiment that a fair amount of errors is due to the erroneous effect of the general-purpose lighting environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.519-522
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• 2004

본 논문에서는 외향 기반 접근법을 기반으로 한 로봇의 위치 추정 알고리즘을 제안한다. 로봇이 작업을 수행할 공간에서 강한 상관관계를 갖는 영상들을 취득하여 eigenspace로 투영 시킴으로써 주성분의 추출을 수행한다. 이 추출된 주성분은 신경 회로망을 이용해 eigenspace에서의 연속 외향 함수(continuous appearance function)로 나타낼 수 있다. 로봇의 위치 추정을 위해 새로운 영상이 주어지면 이것을 eigenspace로 투영 시킨 후 연속 외향 함수를 통해 로봇의 현재 위치를 추정한다. 최종적으로는, 영상안의 데이터에 칼만 필터를 적용함으로써 로봇의 정확한 위치와 영상으로 획득된 정보 사이의 오차를 이용하여 보다 정확한 이동 로봇의 위치를 추정하는 알고리즘을 제안한다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.10
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• pp.69-75
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• 2008

This paper presents an algorithm robust to error for estimating partial discharge (PD) location using acoustic emission sensors. In operating transformers, the velocity computing of the acoustic signal is difficult because the temperature of the Insulation oil is not homogeneous. So, some error occurs in the process. Therefore, the algorithm estimating PD location must consider this error to provide maintenance person with useful information. The conventional algorithm shows the PD position as a point, while the new algorithm using LookUp-Table(LUT) shows PD position as error-map visually. The error-map is more useful than the conventional result because of robustness to error. Also, we compared performance of them, by adding error to data on purpose.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.715-722
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• 2016

In this paper, by applying the linear least squared error algorithm, we derive an estimation technique for three dimensional target location when a number of radars are used in detecting a target. The proposed technique is then enhanced by combining GPS information and by assigning variable weights to information sources. The enhanced performance of proposed techniques is confirmed via simulation. It is also observed from simulation results that the performance is robust to the uncertainty of information.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.191-196
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• 2016

A development on the indoor positioning technologies and services has been proceeded very actively. Among the several positioning technologies, the TDOA(Time Difference of Arrival) technology using acoustic signal has the best positioning performance. Because so many people use their own smartphones, the location of the smartphone is important, and the TDOA technology should be employed to use the acoustic signal for the positioning. For the digital signal processing with the acoustic signal, the signal should be sampled, and as the sampling rate increases, the positioning accuracy could be improved instead of processing time burden. In this paper, the position estimation error according to the sampling rate is analyzed, and the appropriate sampling rate for the positioning system is proposed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.3
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• pp.28-39
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• 2010

In this paper, a new method to estimate MU (motor unit) location in the short head of BIC (biceps brachii) muscle using surface EMG (electromyogram) is proposed. The SMUAP (single motor unit action potential) is generated from a MU located at certain depth from the skin surface. The depth is referred as MU location. For estimating muscle force precisely, the information of the MU location is required. The reference SMUAPs are simulated based on anatomical structure of human muscle, and compared with acquired real EMG signals using 3-channel surface EMG electrode. The proposed method was compared with the results of previous researchers and verified its accuracy by computer simulation. From the simulation result in case of the MU located in 8[mm], the average estimation error of proposed method was 0.01[mm]. But the average estimation error of Roeleveld's method was 2.33[mm] and Akazawa's method was 1.70[mm]. Therefore the proposed method was more accurate than the methods of previous researchers.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.76-84
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• 1999

This paper presents an integrated method for aircraft position estimation using sequential aerial images. The proposed integrated system for position estimation is composed of two parts: relative position estimation and absolute position estimation. Relative position estimation recursively computes the current position of an aircraft by accumulating relative displacement estimates extracted from two successive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameter estimates as an aircraft goes on navigating, resulting in large position error. Therefore absolute position estimation is required to compensate for the position error generated in relative position estimation. Absolute position estimation algorithms by image matching or digital elevation model (DEM) matching are presented. In image matching, a robust oriented Hausdorff measure (ROHM) is employed whereas in DEM matching an algorithm using multiple image pairs is used. Computer simulation with four real aerial image sequences shows the effectiveness of the proposed integrated position estimation algorithm.