• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1926-1933
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• 2022

Parameterized multichannel Wiener filter (PMWF) is a linear filter that can control the trade-off between residual noise and signal distortion using the embedded parameter. To apply the PMWF to noisy inputs, accurate noise estimation is important and multichannel minima-controlled recursive averaging (MMCRA) is widely used. However, in the case of the MMCRA, the accuracy of noise estimation decreases when a directional interference is involved into the array inputs. Consequently, the performance of the PMWF is degraded. Therefore, we propose a noise power spectral density (PSD) estimation method for the PMWF in this paper. The proposed method is based on a consecutive process of eigenvalue decomposition on noisy input PSD, estimation of the target component contribution using directional information, and exponential weighting for improved estimation of the target contribution. For evaluation, four objective measures were compared with the MMCRA and we verify that the PMWF with the proposed noise estimation method can improve performance in environments where directional interfereces exist.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.05a
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• pp.257-262
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• 2008

This study presents a detailed analysis of aircraft engine maintenance cost based on the relationships between engine performance and geometric parameters. Some trend equations based on the engine performance and maintenance database were developed for the estimation of shop-visit interval, work-scope, man-hours, material cost and Life Limited Part cost. The results show that this approach can give a more reasonable and detailed estimation of engine maintenance cost than older empirical methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.808-810
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• 2011

The background estimation algorithms had a significant impact on the performance of image processing and recognition. In this paper, background estimation algorithms were analysis of complexity and performance as preprocessing of image recognition. It was evaluated the performance of Gaussian Running Average, Mixture of Gaussian, and KDE algorithm. The simulation results show that KDE algorithm outperforms compared to the other algorithms.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.2
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• pp.217-222
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• 2004

In this paper, the efficient channel estimation schemes for DRM system(AM band digital radio broadcasting standard) are investigated. In frequency domain, by means of the linear interpolation, the second order interpolation, cubic spline interpolation, and time domain interpolation, the channel impulse response is estimated respectively to compensate the attenuation due to the fading. And in time domain, the frequency channel impulse response is averaged to reduce the attenuation due to the AWGN. By the simulation, the performance of MSE, BER and the complexity of calculation is compared and analyzed for each interpolation scheme.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.34-39
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• 1996

Target state estimation is a fundamental problem of the sonar signal processing. In this paper, the covariance analysis techniques are applied to enhance the performance of the target state estimation of a monopulse sonar system. MOST, the artificial target signal generator based on the highlight model is used to generate signals in various target states. The performance of the developed method has been evaluated by applying it to the various S/N. The enhanced performance of the covariance analysis method presented in this paper is discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.25-33
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• 2018

In this paper, we propose an iterative self-interference (SI) channel estimation method for in-band full-duplex cellular systems that employ orthogonal frequency division multiple access (OFDMA) on downlink (DL) and single-carrier frequency division multiple access (SC-FDMA) on uplink (UL), as in Long Term Evolution (LTE) systems. The proposed method first acquires coarse estimates of SI channels using DL signals and UL pilots, which are known to the base stations, and then refines the estimates by consecutively exploiting averaging in the frequency domain and channel truncation in the time domain. In addition, the method enhances the estimates further by iteratively executing this estimation procedure, and does not require any radio resources dedicated to SI channel estimation. Simulation results demonstrate that by significantly improving the SI channel estimation performance without requiring exact knowledge of the SI channel length, the proposed method achieves UL channel estimation performance and signal-to-interference-plus-noise ratio (SINR) performance very close to those in perfect SI cancellation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.4
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• pp.364-374
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• 2012

The purpose of this study is to perform the reliability-corrected development cost estimation of the launch vehicle at the conceptual design phase. In order to estimate the launch vehicle development cost, the estimation method based on the independent variable such as the rocket performance and dry mass has been mainly implemented up to now. This approach has made the approximate cost estimation possible, however, the cost variation according to the reliability requirement could not be reflected. In this paper, the cost estimation methodology that introduces the reliability factor in addition to the performance and mass in the TRANSCOST model is presented in order to improve the limitation of current cost estimation method. The development cost of KSLV(Korea Space Launch Vehicle)-II is estimated on the basis of this newly implemented concept with reliability as an added parameter.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.565-573
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• 2008

This paper proposes noise reduction methods to improve the channel estimation performance in Equalization On-Channel Repeater (E-OCR) for Terrestrial-Digital Multimedia Broadcasting (T-DMB) system. In the E-OCR for T-DMB system, the channel estimation is performed by the pilot signal extraction and the channel coefficient estimation. Since the performance of the channel estimation highly depends on the estimated channel coefficients whose accuracy is associated with the received signal-to-noise ratio (SNR), it is important to reduce noise existing at the estimated channel coefficients. To reduce such noise components, various noise reduction methods of the estimated channel coefficients based on the M -point weighted moving average are proposed. Computer simulations show that the proposed methods improve the estimation performance by more than 2 to 3 dB in terms of the symbol error rate after equalization.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.631-644
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• 2022

This paper considers robust estimation of the sparse vector autoregressive model (sVAR) useful in high-dimensional time series analysis. First, we generalize the result of Xu et al. (2008) that the adaptive lasso indeed has robustness in sVAR as well. However, adaptive lasso method in sVAR performs poorly as the number and sizes of outliers increases. Therefore, we propose new robust estimation methods for sVAR based on least absolute deviation (LAD) and Huber estimation. Our simulation results show that our proposed methods provide more accurate estimation in turn showed better forecasting performance when outliers exist. In addition, we applied our proposed methods to power usage data and confirmed that there are unignorable outliers and robust estimation taking such outliers into account improves forecasting.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.