• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.7-12
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• 2019

Ambient backscatter communication is limited to channel estimation technique through a pilot signal, which is a channel estimation method in current RF communication, due to transmission power efficiency. In a limited transmission power environment, the research of traditional ambient backscatter communication has been studied assuming that it is an ideal channel without signal distortions due to channel conditions. In this paper, we propose an expectation-maximization(EM) algorithm, one of the blind channel estimation techniques, as a channel estimation method in ambient backscatter communication system which is the state of channel following normal distribution. In the proposed system model, the simulations confirm that channel estimate through EM algorithm is approaching the lower bound of the mean square error compared with the Bayesian Cramer-Rao Boundary(BCRB) to check performance. It shows that the channel parameter can be estimated in the ambient backscatter communication system.

• ETRI Journal
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• v.33 no.1
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• pp.27-31
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• 2011

This paper addresses estimating the frequency of a cisoid in the presence of white Gaussian noise, which has numerous applications in communications, radar, sonar, and instrumentation and measurement. Due to the nonlinear nature of the frequency estimation problem, there is threshold effect, that is, large error estimates or outliers will occur at sufficiently low signal-to-noise ratio (SNR) conditions. Utilizing the ideas of averaging to increase SNR and weighted linear prediction, an optimal frequency estimator with smaller threshold SNR is developed. Computer simulations are included to compare its mean square error performance with that of the maximum likelihood (ML) estimator, improved weighted phase averager, generalized weighted linear predictor, and single weighted sample correlator as well as Cramer-Rao lower bound. In particular, with smaller computational requirement, the proposed estimator can achieve the same threshold and estimation performance of the ML method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.95-102
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• 2003

To define an analytical model for a structural system or to assess damage in the system, system identification(SI) methods have been developed and widely applied. The paper presents a method of determining optimal sensor location(OSL) based on the maximum likelihood approach, which is applicable to modal SI methods. To estimate unknown parameters reliably, it is necessary that the information provided by the experiment should be maximized. By applying the Cramer-Rao inequality, a Fisher information matrix in terms of the probability density function of measurements is obtained from a lower bound of the estimation error. The paper also proposes a scheme of determining of OSL on damaged structures by using maximum strain energy factor. Simulation studies have carried out to investigate the proposed OSL algorithm for both undamaged and damaged structures.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.445-452
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• 1997

A more generalized version of the information inequality based on diffusivity which is a natural measure of dispersion for median-unbiased estimators developed by Sung et al. (1990) is presented. This non-Bayesian L$_{1}$ information inequality is free from regularity conditions and can be regarded as an analogue of the Chapman-Robbins inequality for mean-unbiased estimation. The approach given here, however, deals with a more generalized situation than that of the Chapman-Robbins inequality. We also develop a Bayesian version of the L$_{1}$ information inequality in median-unbiased estimation. This latter inequality is directly comparable to the Bayesian Cramer-Rao bound due to the van Trees inequality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.234-237
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• 2011

본 논문에서는 모델 기반 카메라 추적 시 필요한, 사전 정의 된 실측 모델의 정확성이 카메라 추적의 정확성에 미치는 영향에 대하여 논의한다. 이를 위하여 모델 기반과 특징점 기반의 카메라 추적에 가중치를 두고 혼합시켜 이용하는 하이브리드 카메라 추적 방법을 사용하고, 이 방법을 활용한 상호작용형 모델링(interactive modeling)을 이용하여 실측 모델을 제작한다. 또한, 상호작용형 모델링 과정에서 생기는 실측 모델의 오차로 인해 발생하는 카메라 추적 오차를 Cramer-Rao 하한(lower bound)을 이용하여 정의하고, 이 둘의 상관관계를 실험적으로 도출한다. 이를 통해 사전 정의된 실측 모델이 가질 수 있는 오차의 하한을 실험적으로 검증한다.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.245-251
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• 2013

This paper addresses the issue of time-difference-of-arrival (TDOA) estimation for complex noncircular signals. First, under the wide-sense stationary assumption, we derive the maximum likelihood (ML) estimator and the Cramer-Rao lower bound for Gaussian noncircular signals in Gaussian circular noise. The ML estimator uses the second-order statistics information of a noncircular signal more comprehensively when compared with the cross-correlation (CC) and the conjugate CC estimators. Further, we present a scheme to modify the traditional signal-selective TDOA methods for noncircular signals on the basis of the cyclostationarity of man-made signals. This scheme simultaneously exploits the information contained in both the cyclic cross-correlation (CCC) and the conjugate CCC of a noncircular signal.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.3
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• pp.15-21
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• 2003

This paper contains a precise calibration technique for the position of seabed acoustic target and theoretical error analysis of calibration results. The target is deployed on seabed as a standalone transponder. The purpose of target is performing accuracy test for active sonar as well as position calibration itself. For the position calibration, relative range between target and test vessel should be measured using target's transponder function. The relative range data combined with vessel position can be converted into a estimated position of target by the application of nonlinear LSE method. The error analysis of position calibration was divided into two stages. One is for relative range estimator and the other for target position estimator. Numerical simulations for position calibration showed good matching between results and developed CRLB.

• ETRI Journal
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• v.33 no.6
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• pp.841-848
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• 2011

A signal-to-noise ratio (SNR) enhancement algorithm using multiple chirp symbols with clock drift is proposed for accurate ranging. Improvement of the ranging performance can be achieved by using the multiple chirp symbols according to Cramer-Rao lower bound; however, distortion caused by clock drift is inevitable practically. The distortion induced by the clock drift is approximated as a linear phase term, caused by carrier frequency offset, sampling time offset, and symbol time offset. SNR of the averaged chirp symbol obtained from the proposed algorithm based on the phase derotation and the symbol averaging is enhanced. Hence, the ranging performance is improved. The mathematical analysis of the SNR enhancement agrees with the simulations.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.429-436
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• 2019

The eLoran system is considered the best alternative because the vulnerability of satellite navigation systems cannot be resolved as perfect. Thus, South Korea is in the process of establishing a testbed of the eLoran system in the West Sea. To provide resilient navigation services to all waters, additional eLoran transmitters are required. However, it is difficult to establish eLoran transmitters because of various practical reasons. Instead, the positioning with NDGNSS/AIS source can expand the coverage and its algorithm with applying continuous waves is under development. Using the already operating NDGNSS reference station and the AIS base station, it is possible to operate the navigation system with higher accuracy than before. Thus, it is crucial to predict the performance when each system is integrated. In this paper, we have developed a simulation tool that can predict the performance of terrestrial integrated navigation system using the eLoran system, maritime NDGNSS station and the AIS station. The esitmated phase error of the received signal is calculated with the Cramer-Rao Lower Bound factoring the transmission power and the atmospheric noise according to the transmission frequency distributed by the ITU. Additionally, the simulation results are more accurate by estimating the annual mean atmospheric noise of the 300 kHz signal through the DGPS signal information collected from the maritime NDGNSS station. This approach can further increase the reliability of simulation results.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.76-84
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• 2013

In the passive emitter localization using instantaneous TDOA (time difference of arrival) and FDOA (frequency difference of arrival) measurements, the estimation accuracy can be improved by collecting additional measurements. To achieve this goal, it is required to increase the number of the sensors. However, in electronic warfare environment, a large number of sensors cause the loss of military strength due to high probability of intercept. Also, the additional processes should be considered such as the data link and the clock synchronization between the sensors. Hence, in this paper, the passive localization of a stationary emitter is presented by using the successive TDOA and FDOA measurements from two moving sensors. In this case, since an independent pair of sensors is added in the data set at every instant of measurement, each pair of sensors does not share the common reference sensor. Therefore, the QCLS (quadratic correction least squares) methods cannot be applied, in which all pairs of sensor should include the common reference sensor. For this reason, a Gauss-Newton algorithm is adopted to solve the non-linear least square problem. In addition, to show the performance of the proposed method, we compare the RMSE (root mean square error) of the estimates with CRLB (Cramer-Rao lower bound) and derived the CEP (circular error probable) planes to analyze the expected estimation performance on the 2-dimensional space.