• ETRI Journal
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• v.40 no.1
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• pp.101-110
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• 2018

In wireless positioning systems using range measurements non-line-of-sight (NLOS) links cause estimation errors. Several studies have attempted to improve the positioning performance by mitigating these NLOS errors. These studies, however, have focused on the performance of a dataset consisting of three or more links. Therefore, measurement errors induced by links are averaged, and a reliable link is not fully utilized in the dataset. This paper proposes a Link Reliability based on Range Measurement (LRRM) scheme, which specifies the relative reliability of each link using residuals. The link reliability becomes the input to a Link Residual Weighting (LRW) scheme, which is also proposed as a weighted positioning scheme. Moreover, LRRM and LRW constitute new turbo positioning, where the estimation errors are reduced considerably by iterative updates.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.231-237
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• 2018

This paper investigates the impact of the channel variations and channel estimation errors on the error performance of convolutional coded STBC systems. We consider the orthogonal Almouti STBC and the quasi-orthogonal Jafarkhani STBC, and the error performance of the convolutional coded STBC system is investigated according to the channel variation and channel estimation error via numerical simulations. Simulation results show that, if the channel variation speed is slow, time diversity effects improve the error performance compared to the static-channel cases. However, if the channel variation speed is fast, unlike ZF or MMSE detection, the conventional STBC detection has the significant performance degradation especially with the quasi-orthogonal Jafarkhani STBC. Further, the error performance of the system is significantly degraded as the channel estimation errors become stronger, regardless of the detection scheme and channel variation speed.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.1-8
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• 2019

Identifying behavioral errors of seafarers that have led to marine accidents is a basis for research into prevention or mitigation of marine accidents. The purpose of this study is to estimate the optimal probability distribution function needed to model behavioral errors of crew members into three behaviors (i.e., Skill-, Rule-, Knowledge-based). Through use of behavioral data obtained from previous accidents, we estimated the optimal probability distribution function for the three behavioral errors and verified the significance between the probability values derived from the probability distribution function. Maximum Likelihood Estimation (MLE) was applied to the probability distribution function estimation and variance analysis (ANOVA) used for the significance test. The obtained experimental results show that the probability distribution function with the smallest error can be estimated for each of the three behavioral errors for eight types of marine accidents. The statistical significance of the three behavioral errors for eight types of marine accidents calculated using the probability distribution function was observed. In addition, behavioral errors were also found to significantly affect marine accidents. The results of this study can be applied to predicting marine accidents caused by behavioral errors.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.149-160
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• 2015

This study aims to estimate the forest volumes of the upper region of Nam-Han River in ecosystem zoning by forest types and age classes, and to suggest the optimal estimation method through the comparison of the standard errors according to the spatial unit. In the estimation of forest volumes, we used both of direct estimation, which uses sample plots of the target area only, and synthetic estimation, which includes sample plots of the expanded areas as well as those of the target area. As for the spatial expansion, we applied four standards for synthetic estimator: Mountainous zone, Neighbor ecosystem region, Gangwon province, and Buffer zone. The results show that average forest volume per ha, calculated by direct estimation, was $143.5m^3/ha$, while that by synthetic estimation with each standard, was estimated at $146.9m^3/ha$ by Gangwon province, $144.8m^3/ha$ by Buffer zone, $139.8m^3/ha$ by Neighbor ecosystem region, and $138.6m^3/ha$ by Mountainous zone, respectively. The standard errors of direct estimation was $1.79m^3/ha$, while those of synthetic estimation showed not a great difference among the errors. Meanwhile, considering the standard errors by forest type, the lowest was ${\pm}2.3m^3/ha$ of broad-leaved forest, followed by ${\pm}3.3m^3/ha$ of mixed forest, and ${\pm}4.8m^3/ha$ of coniferous forest.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2657-2675
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• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

• ETRI Journal
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• v.29 no.5
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• pp.559-568
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• 2007

This paper presents a new distortion control scheme with a simple estimation model for the propagation errors incurred by dropping some parts of the bitstream in a frame dropping-coefficient dropping (FD-CD) transcoder. The primary goal of this paper is to facilitate bit-rate conversions and rate-distortion controls in the compressed domain without introducing a full decoding and reencoding system in the pixel domain. First, the error propagation behavior over several frame sequences due to coefficient dropping is investigated on the basis of statistical and empirical properties. Then, such properties are used to develop a simple estimation model for the CD distortion accounting for the characteristics of the underlying coded-frame. Finally, the proposed estimation model allows us to determine the amount of coefficient dropping and to effectively allocate rate-distortions into coded-frames. Experimental results show that the proposed estimation model accurately describes the characteristics of propagation errors adaptively in the compressed domain and can be easily applied to distortion control over different kinds of video sequences.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.169-184
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• 2002

In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• Journal of the Korean Statistical Society
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• v.13 no.2
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• pp.107-113
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• 1984

In a linear regression model the idependent variables are frequently subject to measurement errors. For this case, the problem of estimating unknown parameters has been extensively discussed in the literature while very few has been concerned with the effect of measurement errors on prediction. This paper investigates the behavior of the predicted values of the dependent variable in terms of the average mean square error of prediction (AMSEP). AMSEP may be used as a criterion for selecting an appropriate estimation method, for designing an estimation experiment, and for developing cost-effective future sampling schemes.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.59-61
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• 2004

For automatic landing of small VTOL UAV, it is necessary to calculate the distance from the UAV and the ground. The distance can be generally measured by a ultra-sonic sensor, but the ultra-sonic sensor has errors according to velocity of a sensor board. To compensate these errors, we proposed a sensor fusion method using a Kalman filter.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.187-192
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• 1992

There are several potential error sources that can affect the estimation of the position of an object using combined vision and acceleration measurements. Two of the major sources, accelerometer dynamics and random noise in both sensor outputs, are considered. Using a second-order model, the errors introduced by the accelerometer dynamics are reduced by the smaller value of damping ratio and larger value of natural frequency. A Kalman filter approach was developed to minimize the influence of random errors on the position estimate. Experimental results for the end-point movement of a flexible beam confirmed the efficacy of the Kalman filter algorithm.