• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.382-385
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• 2007

Constantly enhancing positioning accuracy by the Global Positioning System (GPS) technique is of great importance, but challenging, especially after the GPS positioning technique has been improved considerably during the past two decades. The associated main error sources have been reduced substantially, if not eliminated. Troposhpeic influence with its highly temporal and spatial variability appears to be one of the major error sources. It is hence an increased interest among GPS researchers to reduce the tropospheric influence or delay. Two techniques have been commonly implemented to correct the tropospheric impact. The first technique, known as parameter estimation, characterizes the path delay with empirical models and the parameters of interest are determined from the GPS measurements. The second strategy, termed as external correction, involves independent path delay measurements. The present study is an integration of both techniques in which the parameter estimation as well as external correction are used to correct the path delay for $110{\sim}210$ km range baselines. Twenty-four parameters have been obtained in 24 hours solution by setting the cutoff angle at 3 and 15 degrees for parameter estimation strategy. Measurements from meteorological instruments and water vapor radiometer (WVR) are applied in the GPS data processing, separately, as an external strategy of present research work. Interesting results have been found, indicating more stable repeatability in baseline when the external correction strategy is applied especially with the inclusion of WVR observations. The offset of an order of 1 cm is found in the baselines determined by the two strategies. On the other hand, parameter estimation exhibits more stable in terms of GPS height repeatability. The offset in the GPS height determined by the two strategies is on the order of few centimeters.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.279-284
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• 2017

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.285-291
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• 2017

Many methods have been studied to estimate the time delay between incoming signals to two receivers. In the case of the method based on the channel estimation technique, the relative delay between the input signals of the two receivers is estimated as an impulse response of the channel between the two signals. In this case, the characteristic of the channel has sparsity. Most of the existing methods do not take advantage of the channel sparseness. In this paper, we propose a time delay estimation method using BPD (Basis Pursuit Denoising) optimization technique, which is one of the sparse signal optimization methods, in order to utilize the channel sparseness. Compared with the existing GCC (Generalized Cross Correlation) method, adaptive eigen decomposition method and RZA-LMS (Reweighted Zero-Attracting Least Mean Square), the proposed method shows that it can mitigate the threshold phenomenon even under a white Gaussian source, a colored signal source and oceanic mammal sound source.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.221-225
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• 2005

This paper proposes a gain scheduled control technique using time-delay for the nonlinear system with plant uncertainties and unexpected disturbances. The time delay-based gain scheduled control depends on a direct estimation of a function representing the effect of uncertainties. The information from the estimation is used to cancel the unknown dynamics and the unexpected disturbances simultaneously. The proposed estimation scheme with a finite convergence time is formulated in order to estimate the unborn scheduling variable variation. In other words, the time delay-based gain scheduled control uses the past observation of the system's response and the control input to directly modify the control actions rather than to adjust the controller gains or to identify system parameters. It has a simple structure so as to minimize the computational burden. The benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with plant uncertainties and external disturbances, and the proposed controller is compared with the conventional state feedback controller.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1271-1279
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• 2017

A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMA-type robot manipulator.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.406-413
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• 2024

The proposed method uses Generalized Cross Correlation - Phase Transform (GCC-PHAT) method with nonlinear preprocessing and a frequency domain low-pass filter. In this paper, by reinterpreting the calculation process of GCC-PHAT as DFT, we derive that there is an effective frequency band used for time delay estimation in GCC-PHAT, and by using only the effective band using a low-pass filter, the noise component is reduced and it improvesthe time delay performance in impulsive noise environments. By comparing the proposed method with the traditional GCC-PHAT in an impulsive noise environment, we show that the GCC-PHAT becomes more robust to the impulsive noise.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.52-59
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• 1987

A new on-line estimation algorithm for a time varying time delay is proposed. This algorithm is based on the concept of minimization of prediction error. As only the parameters directly related to the poles and zeros of the process are estimated in the algorithm, persistently exciting condition for the convergence of parameters can be less restrictive. Under some assumptions which is necessary in adaptive control, it is shown that this algorithm estimates time varying time delay accurately. In view of computational burden, this algorithm needs far less amount of calculations than other methods. The larger the time delay is, the more effective this algorithm is . Computer simulation shows good properties of the algorithm. This algorithm can be used effectively in adaptive control of large dead time processes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.629-634
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• 2008

In this paper, we propose a simple numerical formula which can estimate the additional delay time due to interconnection branches in general source-termination scheme. We show that interconnection branches have influence on both signal quality and time delay. Using the proposed numerical formula, time delay can be easily predicted by system designers.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.12-19
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• 2017

In this paper a super-resolution time delay estimation algorithm that estimates the time delays of spread spectrum signals using sparse signal reconstruction approach is introduced. So far, the correlation method has been mostly used to estimate the time delays of spread spectrum signals. However it fails to accurately estimate the time delays in the case where the signals are spaced within approximately 1 PN chip duration and a further processing should be applied to the correlation outputs in order to enhance the resolution capability. Recently sparse signal approaches attract much interest in the area of directions-of-arrival estimation, of which SPICE is the most representative. Thus we introduce a super-resolution time delay estimation algorithm based on the SPICE approach and compare its performance with that of MUSIC algorithm by applying them to the ISO/IEC 24730-2.1 RTLS system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8A
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• pp.813-819
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• 2007

In this paper, the effect of a propagation delay resulting from the use of an OFDM-based cellular system with a transparent mobile multi-hop relay(MMR) is initially analyzed. Then, channel estimation techniques, a least square(LS) method and a minimum mean square error(MMSE) method, for the OFDM systems with throughput enhancement(TE) MMR or cooperative MMR are proposed. The proposed channel estimation techniques can overcome the performance degradation caused by the propagation delay in TE MMR or cooperative MMR systems. It is demonstrated by computer simulation that the proposed channel estimation techniques for OFDM systems with transparent MMR are superior to the conventional techniques in terms of mean square error(MSE) and bit error rate(BER).