• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.163-169
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• 2020

The asynchronous bistatic sonar needs to estimate direct blast arrival time at a receiver to localize targets, and therefore the direct blast arrival time estimation error could be added to target localization error in comparison with synchronous system. Direct blast especially appears as several peaks at the matched filter output by multipath, thus we compared the first peak detection technique and the maximum peak detection technique of those peaks for direct blast arrival time estimation through sea trial data. The test was performed in a shallow sea with bistatic sonar made up of spatially separated source and line array sensors. Line array sensors obtained the target signal which is generated from the echo repeater. As a result, the first peak detection technique is superior to maximum peak detection technique in direct blast arrival time estimation error. The result of this analysis will be used for further research of target tracking in the asynchronous bistatic sonar.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.504-512
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• 2003

In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error which is the difference between an ideally modeled dissolve curve with no correlation and an actual dissolve curve including a correlation. The proposed dissolve detection method consists of two steps. First, candidate dissolve regions are extracted using the characteristics of a downward convex parabola, then each candidate region is verified based oil the dissolve modeling error. If the dissolve modeling error for a candidate region is less than a threshold defined by the target modeling error with a target correlation, the candidate region is determined as a resolve region with a lower correlation than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed method was tested on various types of data and its performance proved to be more accurate and reliable regardless of variation of variance of test sequences when compared with other commonly use methods.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.231-237
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• 2018

This paper investigates the impact of the channel variations and channel estimation errors on the error performance of convolutional coded STBC systems. We consider the orthogonal Almouti STBC and the quasi-orthogonal Jafarkhani STBC, and the error performance of the convolutional coded STBC system is investigated according to the channel variation and channel estimation error via numerical simulations. Simulation results show that, if the channel variation speed is slow, time diversity effects improve the error performance compared to the static-channel cases. However, if the channel variation speed is fast, unlike ZF or MMSE detection, the conventional STBC detection has the significant performance degradation especially with the quasi-orthogonal Jafarkhani STBC. Further, the error performance of the system is significantly degraded as the channel estimation errors become stronger, regardless of the detection scheme and channel variation speed.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.81-86
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• 2015

GPS position errors were corrected for guidance of autonomous vehicles. From the vision, we can obtain the lateral distance from the center of lane and the angle difference between the left and right detected line. By using a controller which makes these two measurements zero, a lane following system can be easily implemented. However, the problem is that if there's no lane, such as crossroad, the guidance system of autonomous vehicle does not work. In addition, Line detection has problems working on curved areas. In this case, the lateral distance measurement has an error because of a modeling mismatch. For this reason, we propose GPS error correction filter based on curve-modeled lane detection and evaluated the performance applying it to an autonomous vehicle at the test site.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.137-146
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• 1997

The simplest bit error detection scheme is to append a parity bit to the end of a bit sequence. In this paper an error correction technique with the use of a parity bit is proposed, and the performance of the proposed system is analyzed. The error probability of the proposed system is compared with the output of computer simulation of the proposed system. It is also compared with the error probability of error at BPSK system, and the signal-to-noise ratio gain is showed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.41-50
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• 2014

In this paper, we proposed an error detection in Gaussian normal basis multiplier over $GF(2^n)$. It is shown that by using parity prediction, error detection can be very simply constructed in hardware. The hardware overheads are only one AND gate, n+1 XOR gates, and one 1-bit register in serial multipliers, and so n AND gates, 2n-1 XOR gates in parallel multipliers. This method are detect in odd number of bit fault in C = AB.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1299-1307
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• 2014

In this work, an appropriate analysis model of a precise foot sensor with low detection pressure capability under a low range of variation in the dimensional variables was proposed. With a simple two-dimensional model, it was found that a remarkably high error level sometimes occurred between the analysis and experimental results. In order to overcome the error and improve the performance, a three-dimensional model was introduced, and the detection pressure and sensor characteristics were compared with those of the experimental results, which showed its enhanced performance with less error and higher precision.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.22-28
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• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.371-378
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• 2002

This paper presents the rapid and accurate algorithm for fault detection and location estimation in the transmission line. This algorithm uses wavelet transform for fault detection and harmonics elimination and utilizes least square error method for fault impedance estimation. Wavelet transform decomposes fault signals into high frequence component Dl and low frequence component A3. The former is used for fault phase detection and fault types classification and the latter is used for harmonics elimination. After fault detection, an adaptive data window technique using LSE estimates fault impedance. It can find a optimal data window length and estimate fault impedance rapidly, because it changes the length according to the fault disturbance. To prove the performance of the algorithm, the authors test relaying signals obtained from EMTP simulation. Test results show that the proposed algorithm estimates fault location within a half cycle after fault irrelevant to fault types and various fault conditions.