• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.10
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• pp.848-855
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• 1989

The asymptotic properties of the Overdetermined Yule-Walker (OYW) estimators were studied. A formula was derived for the asymptotic covariance matrix of the estimation errors. It verified the experimentally observed fact that the frequency estimation accuracy is generally improved as the number of Yule-Walker equations is increased. The asymptotic estimation accuracies of the OYW method were compared with the Cramer-Rao low bound.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.125-133
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• 2004

Most of the way shape estimation method using reference sources assume that the reference sources are in the farfield. That is, the reference sources are assumed to be far from the array. However, in applications of the array with reference sources, the reference sources are not far from the way, so that in practical ocean environments, the conventional method using farfield source model fail to estimate the positions of the hydrophones. In this paper, based on the nearfield source model, a subspace-based array shape estimation method was proposed. In the proposed method, nearfield reference source is modeled using the differential time delay at each hydrophone, and nearfield parameters are derived. Using these parameters, a subspace-based array shape estimation method that generalizes the existing farfield subspace fitting method which can work regardless of the range of the source is proposed. The Cramer-Rao lower bound for the proposed method is investigated. The results of the numerical experiments indicate that the proposed method performs well in estimating the shape of a perturbed way regardless of the ranges of the reference sources.

• Journal of Advanced Navigation Technology
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• v.24 no.1
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• pp.47-52
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• 2020

Direction of arrival (DoA) estimation is a scheme of estimating the directions of targets by analyzing signals generated or reflected from the targets and is used in various fields. Artificial neural networks (ANN) is a field of machine learning that mimics the neural network of living organisms. They show good performance in pattern recognition. Although researches has been using ANNs to estimate the DoAs, there are limitationsin dealing with variations of the signal-to-noise ratio (SNR) of the target signals. In this paper, we propose a three-stage ANN algorithm for DoA estimation. The proposed algorithm can minimize the performance reduction by applying the model trained in a single SNR environment to various environments through a 'noise reduction process'. Furthermore, the scheme reduces the difficulty in learning and maintains efficiency in estimation, by employing a process of DoA shift. We compare the performance of the proposed algorithm with Cramer-Rao bound (CRB) and the performances of existing subspace-based algorithms and show that the proposed scheme exhibits better performance than other schemes in some severe environments such as low SNR environments or situations in which targets are located very close to each other.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.424-429
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• 2009

This paper suggests an autocorrelation function (AF) based carrier frequency offset (CFO) estimator based on a training sequence in flat fading channels. The proposed CFO estimator has the reduced computational burdens in the calculation of the AF when compared to AF-based conventional frequency estimators. The simulation results show that the proposed estimator achieves a better performance than the existing estimators. Furthermore, the performance of the proposed method has been observed to lie close to the Cramer-Rao lower bound (CRLB).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.373-379
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• 2019

If two signals with the same single-tone frequency and differing phases impinge simultaneously on an antenna at slightly differing angles, then a large error in the angle estimation might occur if the phase difference is either $0^{\circ}$ or $180^{\circ}$. This phenomenon might arise with an airborne fire-control radar, which has a relatively small bandwidth, for a low-flying target over the sea or terrain surface. In this paper, we show that the $Cram{\acute{e}}r$-Rao lower bound for such a target can be significantly lowered with the use of two frequencies.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.53-58
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• 2012

In this paper, we evaluate and analyze representative estimation methods for the sparse channel. In order to evaluate error performance of matching pursuit(MP) and minimum mean square error(MMSE) algorithm, lower bound of MMSE is determined by Cramer-Rao bound and compared with upper bound of MP. Based on analysis of those bounds, mean square error of MP which is effective in the estimation of sparse channel can be larger than that of MMSE according to the number of estimated tap and signal-to-noise ratio. Simulation results show that the performances of both algorithm are reversed on the sparse channel with Rayleigh fading according to signal-to-noise ratio.

• 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.37 no.1
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• pp.1-10
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• 2015

A blind hopping phase estimator is proposed for the demodulation of received signals in frequency-hopping spread spectrum systems. The received signals are assumed to be bandwidth limited with a shaping filter, modulated as frequency modulation (FM) or binary frequency shift keying (BFSK), and hopped by predetermined random frequency sequences. In the demodulation procedure in this paper, the hopping frequency tracking is accomplished by choosing a frequency component with maximum amplitude after taking a discrete Fourier transform, and the hopping phase estimator performs the conjugated product of two consecutive signals and moving-average filtering. The probability density function and Cramer-Rao low bound (CRLB) of the proposed estimator are evaluated. The proposed scheme not only is very simple to implement but also performs close to the CRLB in demodulating hopped FM/BFSK signals.

• 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.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.284-293
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• 2005

A critical issue in applications involving networks of wireless sensors is their ability to synchronize, and mitigate the fading propagation channel effects. Especially when distributed 'slave' sensors (nodes) reach-back to communicate with the 'master' sensor (gateway), low power cooperative schemes are well motivated. Viewing each node as an antenna element in a multi-input multi-output (MIMO) multi-antenna system, we design pilot patterns to estimate the multiple carrier frequency offsets (CFO), and the multiple channels corresponding to each node-gateway link. Our novel pilot scheme consists of non-zero pilot symbols along with zeros, which separate nodes in a time division multiple access (TDMA) fashion, and lead to low complexity schemes because CFO and channel estimators per node are decoupled. The resulting training algorithm is not only suitable for wireless sensor networks, but also for synchronization and channel estimation of single- and multi-carrier MIMO systems. We investigate the performance of our estimators analytically, and with simulations.