• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.357-358
• /
• 2018

The track radar use the range track loop to track the target range. The bandwidth of the radar range tracker can be determined by tradeoff according to signal to noise ratio and the target range. On the other hand, electronic warfare is carried out to prevent the radar from tracking targets by electronic attack. The deception or noise jamming in electronic warfare can be performed to interfere with the range track loop of the radar. In order to efficiently perform electronic warfare, the bandwidth in radar tracking loop is estimated and can be used for electronic attack. To do this, we have studied the method of estimating the bandwidth of radar tracking loop using the variables that can be gathered in electronic warfare.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.4
• /
• pp.606-614
• /
• 2012

A practical recursive linear robust estimation scheme is proposed for target localization in the sensor network which provides range difference of arrival (RDOA) measurements. In order to radically solve the known practical difficulties such as sensitivity for initial guess and heavy computational burden caused by intrinsic nonlinearity of the RDOA based target localization problem, an uncertain linear measurement model is newly derived. In the suggested problem setting, the target localization performance of the conventional linear estimation schemes might be severely degraded under the low SNR condition and be affected by the target position in the sensor network. This motivates us to devise a new sensor network localization algorithm within the framework of the recently developed robust least squares estimation theory. Provided that the statistical information regarding RDOA measurements are available, the estimate of the proposition method shows the convergence in probability to the true target position. Through the computer simulations, the omnidirectional target localization performance and consistency of the proposed algorithm are compared to those of the existing ones. It is shown that the proposed method is more reliable than the total least squares method and the linear correction least squares method.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.12
• /
• pp.1833-1840
• /
• 2013

A golf ball collecting robot in a golf ball driving range has been recently required because it is safer and more economic than a human being. In this paper, the golf ball recognition and distance estimation system based on a neural network and OpenCV is developed for the robot. The simulation results show that the recognition ratio is over 87% for the distance of less than 120cm and accurate rate for distance estimation is over 85% for golf balls in 30-180cm from a webcam.

• Journal of the Korean Society for Precision Engineering
• /
• v.32 no.4
• /
• pp.377-386
• /
• 2015

Joint force/torque estimation by inverse dynamics is a traditional tool in biomechanical studies. Conventionally for this, kinematic data of human body is obtained by motion capture cameras, of which the bulkiness and occlusion problem make it hard to capture a broad range of movement. As an alternative, inertial motion sensing using cheap and small inertial sensors has been studied recently. In this research, the performance of inertial motion sensing especially to calculate inverse dynamics is studied. Kinematic data from inertial motion sensors is used to calculate ground reaction force (GRF), which is compared to the force plate readings (ground truth) and additionally to the estimation result from optical method. The GRF estimation result showed high correlation and low normalized RMSE(R=0.93, normalized RMSE<0.02 of body weight), which performed even better than conventional optical method. This result guarantees enough accuracy of inertial motion sensing to be used in inverse dynamics analysis.

• The Korean Journal of Applied Statistics
• /
• v.27 no.4
• /
• pp.605-617
• /
• 2014

Small area estimation is a statistical inference method to overcome large variance due to a small sample size allocated in a small area. A shrinkage estimator obtained by minimizing relative error(RE) instead of MSE has been suggested. The estimator takes advantage of good interpretation when the data range is large. A semiparametric estimator is also studied for small area estimation. In this study, we suggest a semiparametric shrinkage small area estimator and compare small area estimators using labor statistics.

• Journal of Advanced Navigation Technology
• /
• v.15 no.6
• /
• pp.962-969
• /
• 2011

This paper proposes the DOA estimation method based on TDOA/AOA for jammer localization method in GBAS environment. The proposed method can effectively estimate DOA of jamming signal as the range for DOA estimation is reduced remarkably by using DOP and 1st approximate solution using TDOA measurements only. Through the proposed method, more precise DOA can be obtained and the performance of jammer localization is increased simultaneously. Also, the effectiveness of proposed method will be confirmed through the simulated results.

• Journal of Advanced Navigation Technology
• /
• v.17 no.4
• /
• pp.386-395
• /
• 2013

This paper proposes a root-assisted MUSIC algorithm which uses a combination of the MUSIC and the root-MUSIC algorithm. This algorithm consists of two steps. Firstly, a coarse DOA is computed by the root-MUSIC algorithm. Secondly, a precise DOA estimation is carried out by the MUSIC algorithm in the reduced searching range. This paper analyzes the accuracy and the resolution performance of the proposed DOA estimation method using a software simulation platform.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.11 no.5
• /
• pp.305-312
• /
• 2016

Modern embedded systems are typically operated by the rechargeable batteries in our daily life. Since charge of batteries is considered as an time consuming task, there have been extensive efforts to manage the charge time from the perspective of materials, circuits, and systems. Estimation of battery charge time is one of the essential information to design the charge circuitry. A compact macro model for the constant-current and constant-voltage charge protocol was recently introduced, which gives us a quick estimation of charge time with similar shape to the famous Peukert's law for discharge time estimation. The CC-CV charging protocol is widely used for Lithium-based batteries and Lead-acid batteries. In this paper, we characterize the lead-acid battery by measurement to extract the model coefficients, which was not covered by the previous studies. By our proposed model, the key coefficient Kcc results in 1.18-1.31, which is little bit higher than that of Lithium batteries. The accuracy of our model is within the range of ${\pm}10%$ error, which is compatible with the other studies such as Peukert's law.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.10
• /
• pp.1874-1881
• /
• 2010

A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

• Earthquakes and Structures
• /
• v.14 no.2
• /
• pp.155-165
• /
• 2018

Methods based on nonlinear static analysis as simple tools could be used for the seismic analysis and assessment of structures. In the present study, capability of the N2 method as a well-known nonlinear analysis procedure examines for the estimation of the damage index of multi-storey reinforced concrete frames. In the implemented framework, equivalent single-degree-of-freedom (SDOF) models are utilized for the global damage estimation of multi-degree-of-freedom (MDOF) systems. This method does not require high computational analysis and subsequently decreases the required time of seismic design and assessment process. To develop the methodology, RC frames with period range from 0.4 to 2.0 s under 40 records are studied. The effectiveness of proposed technique is evaluated through numerical study under near- and far-field earthquake ground motions. Finally, the results of developed models are compared with two other simplified schemes along with nonlinear time history analysis results of multi-storey frames. To improve the accuracy of damage estimation, a modified relation is presented based on the N2 method results for near- and far-field earthquakes.