• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.4
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• pp.318-324
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• 2013

For blind channel equalization, the reliability of signal estimate determines the convergence speed and steady-state performance of the equalizer. Therefore the nonlinear estimator and reference signal being used in signal estimate should be chosen appropriately. In this paper, to increase the reliability of the signal estimate, two errors were obtained by applying coarse signal points and dense signal points respectively to signal estimate, the relative reliabilities of two errors were calculated, then the equalizer was adapted deferentially utilizing the reliabilities. At this point, by applying two errors alternately, two modes of operation were smoothly combined. Through computer simulations the proposed method was confirmed to achieve fast transient state convergence and low steady-state error compared to traditional methods.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.8-13
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• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Journal of Biomedical Engineering Research
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• v.5 no.2
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• pp.133-142
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• 1984

The EMG signal can be considered as a signal source that expresses the intention of man because it is a electrical signal generated when the man contracts muscles. For proportional control of prostheses, the control signal proportional to the mousle contraction level must be estimated. Typically a foul-wave rectifier and low-pass filter are used to estimate the proportional control signal from the EMG signal. In this paper, it is proposed to use a logarithmic transformation and a linear minimum mean square error estimator. A logarithmic transformation maps the myoelectric signal into an additive control signal-plus-noise domain and the Kalman filter is used to estimate the control signal as a linear minimum mean square error estimator. The performance of this estimator is verified by the computer simulation and the estimator is applied to the EMG obtained from the biceps brachii muscle of normal subjects.

• Publications of The Korean Astronomical Society
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• v.20 no.1 s.24
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• pp.109-116
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• 2005

When we measure a source signal in the presence of a background rate that has been independently measured, the usual approach is to obtain an estimate of the background rate by observing an empty part of the sky, and an estimate of the source signal plus background rate by observing the region where a source signal is expected. The source signal rate is then estimated by subtracting the background rate from the source signal plus background rate. However, when the rates or their observation times are small, this procedure can lead to negative estimates of the source signal rate, even when it should produce a positive value. By applying the Bayesian approach, we solve the problem and prove that the most probable value of source signal rate is zero when the observed total count is smaller than the expected background counts. It is also shown that the results from the conventional method is consistent with the most probable value obtained from the Bayesian approach when the source signal is large or the observation time is long enough.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.470-474
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• 1998

In this paper, to estimate the time-varying parameters of speech signal, we use the robust sequential estimator based on t-distribution and, for time-varying signal, introduce the forgetting factor. By using the RSE based on t-distribution with small degree of freedom, we can alleviate efficiently the effects of outliers to obtain the better performance of parameter estimation. Moreover, by the forgetting factor, the proposed algorithm can estimate the accurate parameters under the rapid variation of speech signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.562-570
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• 1997

In Direct Sequence Code Division Multiple Access(DS/CDMA) communication systems, it is important to contraol the power of reverse link channel evenly for overall channel capacity. To control the reverse link powers efficiently, it is necessary to estimate signal quality of each reverse link channel. In this paper, we discuss a method to estimate the signal-to-noise ratio(SNR) for each channel by measuring the powers of pilot and noises. Computer simulations are done to show the effectiveness of the scheme.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.135-140
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• 2017

This paper proposes a signal merging algorithm to increase the signal-to-noise ratio (SNR) of a GPS correlator output to estimate the roll angle of a rotating vehicle in a weak GPS signal environment. Rotation Locked Loop (RLL) algorithm is used to estimate a roll angle using the characteristics that the power of the GPS signal measured at the receiver of a rotating vehicle varies periodically. First, delay times are calculated to synchronize GPS signals using satellites' and receiver's positions and the rotation frequency of a vehicle, and then correlator outputs are delayed in time and merged with each other, resulting in the increase of an SNR in a correlator output. Finally, simulations are conducted and the performance of the proposed algorithm is validated.

• Journal of Mechanical Science and Technology
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• v.16 no.11
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• pp.1379-1394
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• 2002

In case of a single input single output (SISO) system with a nonlinear term, a signal compression method is useful to identify a system because the equivalent impulse response of linear part from the system can be extracted by the method. However even though the signal compression method is useful to estimate uncertain parameters of the system, the method cannot be directly applied to a unique system with hysteresis characteristics because it cannot estimate all of the two different dynamic properties according to its motion direction. This paper proposes a signal compression method with a pre-processor to identify a unique system with two different dynamics according to its motion direction. The pre-processor plays a role of separating expansion and retraction properties from the system with hysteresis characteristics. For evaluating performance of the proposed approach, a simulation to estimate the assumed unknown parameters for an arbitrary known model is carried out. A motion platform with several single-rod cylinders is a representative unique system with two different dynamics, because each single-rod cylinder has expansion and retraction dynamic properties according to its motion direction. The nominal constant parameters of the motion platform are experimentally identified by using the proposed method. As its application, the identified parameters are applied to a design of a sliding mode controller for the simulator.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.521-530
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• 2005

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry(TFDR), isproposed to detect and estimate a fault in a transmission line. Traditional reflectometry methodologies have been achieved either in the time domain or in the frequency domain only. However, the TFDR can jump over the performance limits of the traditional reflectometry methodologies because the acquired signal is analyzed in time and frequency domain simultaneously. In the TFDR, the new reference signal and the novel TFDR algorithm are proposed for analyzing the acquired signal in the time-frequency domain. Because the reference signal of Gaussian envelop chirp signal is localized in the time and frequency domain simultaneously, it is suitable to the analysis in the time-frequency domain. In the proposed TFDR algorithm, the time-frequency distribution function and the normalized time-frequency cross correlation function are used to detect and estimate a fault in a transmission line. That algorithm is verified for real-world coaxial cables which are typical transmission line with different types of faults by the TFDR system composed of real instruments. The performance of the TFDR methodology is compared with that o( the commercial time domain reflectomeoy(TDR) experiments, so that concludes the TFDR methodology can detect and estimate the fault with smaller error than TDR methodology.

• Journal of KSNVE
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• v.6 no.3
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• pp.357-362
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• 1996

The magnetic levitation system has great advantages, such as little friction, no lubrication, no noise and so on. But the magnetic levitation system need a stabilizing controller because it is a unstable, system in natural and it need a sensor for displacement measurement to control the system. In this paper, we proposed a sensorless method to measure the gap between the magnetic pole and the levitated object with application the inductance characteristic which vary according to gap. We made a driving circuit which supply simultaneously the control input PWM(Pulse Width Modulation) signal and the carrier PWM signal to estimate the gap. Because the inductance is a function of gap, and the current of the carrier signal is a function of the inductance, we could estimate the gap from the measurement of the current of the carrier signal. Finally, we investigated the validity of the proposed method through the experimental results.