• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.148-155
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• 2015

The Levenberg-Marquardt method is a well known solution about the least square problem. However, in a Target Motion Analysis(TMA) application most of researches have used the Gauss-Newton method as a batch estimator, which of inverse matrix calculation may causes instability problem. In this paper, Levenberg-Marquardt method is applied to TMA problem to prevent its divergence. In experiment, its performance is compared with Gauss-Newton in domain of range, course and speed. Monte Carlo simulation reveals the convergence time and reliability of the TMA based on Levenberg-Marquardt.

• Journal of Power Electronics
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• v.11 no.4
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• pp.464-470
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• 2011

In this paper, the feasibility of applying a position sensorless control technique to hybrid electric vehicles (HEVs) is practically evaluated. The proposed position estimator has a straightforward structure with properties that combines the model and the saliency tracking-based rotor position estimation for interior permanent magnet synchronous motors (IPMSMs). The proposed method can be used in the event of sensor loss or sensor recovery to sustain continuity of operations. The developed system takes into account the estimated position transition between two distinct sensorless methods. The transition is enhanced by introducing a synchronized transition algorithm based on a single tracking observer. Extensive experimental results are presented to verify the principles and show a reliable estimation performance over the entire speed range including standstill under 150% load conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1111-1117
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• 2003

The maximum Doppler frequency, or equivalently, the mobile speed is very useful information to optimize the performance of many wireless communication systems. However, the performance of a maximum Doppler frequency estimator is limited since it requires an estimate of the signal-to-noise ratio (SNR) of the channel environment. In this paper, the improved method for the maximum Doppler frequency estimations based on the decision feedback Doppler adaptive band-limit (DF-DABL) method is proposed. To reduce the effect of additive noise, the proposed algorithm uses a novel Doppler adaptive band-limit (DABL) technique. The distortion due to the additive noise is drastically removed by the proposed DF-DABL method. Especially, the DF-DABL method does not need any other channel information such as SNR.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1681-1690
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• 2013

In this paper, a design of speed and position controller based on the EKF(Extended Kalman Filter) for sensorless control in IPMSM(Interior Permanent Magnet Synchronous Motor) is proposed. The proposed method subdivides the state estimation interval for improving the accuracy of state estimation. and each subdivided interval estimated first order term using Taylor series. The proposed state estimator comparison with the second-order extended Kalman filter reduced calculation amount of a priori estimation. And the simulation results were proved that The accuracy of priori estimation is increased.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.281-288
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• 2004

In this paper, we consider the diversity combining method for multiple symbol differential detection (MSDD) over the slow fading diversity channel. Though the performance of the optimum maximum-likelihood sequence estimator for MSDD approaches the performance of maximal-ratio combining with differential encoding, the complexity increases exponentially as the size of MSDD block is increased. This new pre-combining method can make use of the efficient MSDD algorithm that has a complexity increasing linearly with the block length or MSDD. Thus, in many wireless scenarios where it is not possible to perform coherent detection. this pre-combined diversity MSDD can be applied to obtain substantial gain compare to conventional differential detection.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.455-467
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• 2017

When performing target detection using hyperspectral imagery, a feature extraction process is necessary to solve the problem of redundancy of adjacent spectral bands and the problem of a large amount of calculation due to high dimensional data. This study proposes a new band selection method using the $L_{2,1}$-norm regression model to apply the feature selection technique in the machine learning field to the hyperspectral band selection. In order to analyze the performance of the proposed band selection technique, we collected the hyperspectral imagery and these were used to analyze the performance of target detection with band selection. The Adaptive Cosine Estimator (ACE) detection performance is maintained or improved when the number of bands is reduced from 164 to about 30 to 40 bands in the 350 nm to 2500 nm wavelength band. Experimental results show that the proposed band selection technique extracts bands that are effective for detection in hyperspectral images and can reduce the size of the data without reducing the performance, which can help improve the processing speed of real-time target detection system in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6A
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• pp.341-350
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• 2003

In this paper, we evaluate the performance of a moving average (MA) channel estimation filter when space-time block coding transmit diversity (STBC-TD) is applied to the wideband direct sequence code division multiple access (WCDMA) forward link. And we present the infinite impulse response (IIR) filter scheme that can reduce the required memory buffer and the channel estimation delay time. This paper also compares the performance between MA filter scheme and IIR filter scheme in various Rayleigh fading channel environments through the bit error rate (BER) and the frame error rate (FER). Extensive computer simulation results show that transmission with STBC-TD provides a significant gain in performance over no transmit diversity technique, particularly at pedestrian speeds. If STBC-TD technique is employed in the channel estimator based on MA filter, it provides considerable performance gains against Rayleigh fading and reduces the optimum filter tap number. Consequently, the channel estimation delay time and the complexity of the receiver are reduced. In addition, the channel estimator based on IIR filter has the advantages such as little memory requirement and no delay time compared to the MA scheme. However, IIR filter coefficients is very sensitive to the mobile speed change and it exerts a serious influence upon the performance. For that reason, it is important to set uP the optimum IIR filter coefficients.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.8-15
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• 2019

The PM synchronous motor drives with vector control have been applied to wide fields of industry applications due to its high efficiency. The rotor position information for vector control of a PM synchronous motor is detected from the rotor position sensors or rotor position estimators. The sensorless control based on the mathematical model of PM synchronous motor is generally used and it can be classified into back EMF -based sensorless control and magnet flux-based sensorless control. The rotor position estimating performance of the back EMF-based sensorless control is deteriorated at low speeds since the magnitude of back EMF is proportional to the motor speed. The magnitude of the magnet flux for estimating rotor position in the flux-based sensorless control is independent on the motor speed so that the estimating performance is excellent for wide speed ranges. However, the estimation performance of the model-based sensorless control may be influenced by the motor parameter variation since the rotor position estimator uses the mathematical model of the PM synchronous motor. In this paper, the rotor position estimation performance for the back EMF based- and flux-based sensorless controls is analyzed theoretically and is compared through the simulation and experiment when the motor parameters including stator resistance and inductance are varied.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1247-1267
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• 2014

Real-Time Hybrid Simulation (RTHS) is a novel approach conceived to evaluate dynamic responses of structures with parts of a structure physically tested and the remainder parts numerically modelled. In RTHS, delay estimation is often a precondition of compensation; nonetheless, system delay may vary during testing. Consequently, it is sometimes necessary to measure delay online. Along these lines, this paper proposes an online delay estimation method using least-squares algorithm based on a simplified physical system model, i.e., a pure delay multiplied by a gain reflecting amplitude errors of physical system control. Advantages and disadvantages of different delay estimation methods based on this simplified model are firstly discussed. Subsequently, it introduces the least-squares algorithm in order to render the estimator based on Taylor series more practical yet effective. As a result, relevant parameter choice results to be quite easy. Finally in order to verify performance of the proposed method, numerical simulations and RTHS with a buckling-restrained brace specimen are carried out. Relevant results show that the proposed technique is endowed with good convergence speed and accuracy, even when measurement noises and amplitude errors of actuator control are present.

• Journal of The Korean Astronomical Society
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• v.42 no.3
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• pp.61-69
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• 2009

Transverse velocity vectors can be determined from a pair of images successively taken with a time interval using an optical flow technique. We have tested the performance of the new technique called NAVE (non-linear affine velocity estimator) recently implemented by Chae & Sakurai using real image data taken by the Narrowband Filter Imager (NFI) of the Solar Optical Telescope (SOT) aboard the Hinode satellite. We have developed two methods of estimating the errors in the determination of velocity vectors, one resulting from the non-linear fitting ${\sigma}_{\upsilon}$ and the other ${\epsilon}_u$ resulting from the statistics of the determined velocity vectors. The real error is expected to be somewhere between ${\sigma}_{\upsilon}$ and ${\epsilon}_u$. We have investigated the dependence of the determined velocity vectors and their errors on the different parameters such as the critical speed for the subsonic filtering, the width of the localizing window, the time interval between two successive images, and the signal-to-noise ratio of the feature. With the choice of $v_{crit}$ = 2 pixel/step for the subsonic filtering, and the window FWHM of 16 pixels, and the time interval of one step (2 minutes), we find that the errors of velocity vectors determined using the NAVE range from around 0.04 pixel/step in high signal-to-noise ratio features (S/N $\sim$ 10), to 0.1 pixel/step in low signa-to-noise ratio features (S/N $\sim$ 3) with the mean of about 0.06 pixel/step where 1 pixel/step corresponds roughly to 1 km/s in our case.