• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.11 no.5
• /
• pp.813-821
• /
• 2000

The engineering of satellite communication systems at frequencies above 10GHz requires a method for estimating rain-caused outage probabilities on the earth-satellite path. A procedure for predicting a rain attenuation distribution from a point rainfall rate distribution is, therefore, needed. In order to predict rain attenuation on the satellite link, several prediction models such as ITU-R, Global, SAM, DAH model, have been developed and used at a particular propagation condition, they may not be appropriate to a propagation condition in Korean territory. In this paper, a new rain attenuation prediction method appropriate to a propagation condition in Korea is introduced. Based on the results from ETRI measurements, a new method has been derived for an empirical approach with an identification on the horizontal correction factor as in current ITU-R method, and the vertical correction factor has been suggested with decreasing power law as a function of rainfall rate. This proposed model uses the entire rainfall rate distribution as input to the model, while the ITU-R and DAH model approaches only use a single 0.01% annual rainfall rate and assume that the attenuation at other probability levels can be determined from that single point distribution. This new model was compared with several world-wide prediction models. Based on the analysis, we can easily know the importance of the model choice to predict rain attenuation for a particular location in the radio communication system design.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.10
• /
• pp.2338-2356
• /
• 2013

In cognitive radio networks, acquiring the position information of the primary user is critical to the communication of the secondary user. Localization of primary users can help improve the efficiency with which the spectrum is reused, because the information can be used to avoid harmful interference to the network while simultaneity is exploited to improve the spectrum utilization. Despite its inherent inaccuracy, received signal strength based on range has been used as the standard tool for distance measurements in the location detection process. Most previous works have employed the path-loss propagation model with a fixed value of the path loss exponent. However, in actual environments, the path loss exponent for each channel is different. Moreover, due to the complexity of the radio channel, when the number of channel increases, a larger number of RSS measurements are needed, and this results in additional energy consumption. In this paper, to overcome this problem, we propose using the Bayesian compressive sensing method with a calibrated path loss exponent to improve the performance of the PU localization method.

• ETRI Journal
• /
• v.38 no.4
• /
• pp.634-644
• /
• 2016

Channel-based radio-frequency fingerprinting such as a channel impulse response (CIR), channel transfer function (CTF), and frequency coherence function (FCF) have been recently proposed to improve the accuracy at the physical layer; however, their empirical performance, advantages, and limitations have not been well reported. This paper provides a comprehensive empirical performance evaluation of RF location fingerprinting, focusing on a comparison of received-signal strength, CIR-, CTF-, and FCF-based fingerprinting using the weighted k-nearest neighbor pattern recognition technique. Frequency domain channel measurements in the IEEE 802.11 band taken on a university campus were used to evaluate the accuracy of the fingerprinting types and their robustness to human-induced motion perturbations of the channel. The localization performance was analyzed, and the results are described using the spatial and temporal radio propagation characteristics. In particular, we introduce the coherence region to explain the spatial properties and investigate the impact of the Doppler spread in time-varying channels on the time coherence of RF fingerprint structures.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1615-1620
• /
• 2003

Kinematic calibration is a process whereby the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. Measuring all components of Cartesian posture, particularly the orientation, can be difficult. With partial pose measurements, all parameters may not be identifiable. This paper proposes a new device that can identify all kinematic parameters with partial pose measurements. Study is performed for a six degree-of-freedom fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector's motion to five degree-of-freedom and can measure position of the end-effector and one of its rotations. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise. Intrinsic inaccuracies of the device can significantly deteriorate the calibration results. A measurement procedure is proposed and formulations of cost functions are discussed to prevent propagation of the inaccuracies to the calibration results.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.27 no.1
• /
• pp.39-45
• /
• 2003

As the size of a combustor decreases to a MEMS scale, heat loss increases and becomes a dominant effect on the performance of the devices. Existing models, however, are not adequate to predict the heat transfer and combustion processes in such small scales. In the present study, a semi-empirical model to calculate heat loss from a micro combustor is described. The model derives heat transfer coefficients that best fits the heat loss characteristics of a micro combustor that is represented by transient pressure record after combustion is completed. From conservation of energy equation applied to the burned gas inside the combustor, a relationship between pressure and heat transfer is reduced. Two models for heat transfer coefficients were tested; a constant and first order polynomial of temperature with its coefficients determined from fitting with measurements. The model was tested on a problem of cooling process of burnt gas in a micro combustor and comparison with measurements showed good agreements. The heat transfer coefficients were used for combustion calculation in a micro vessel. The results showed the dependence of flame speed on the scale of the chamber through enhanced heat loss.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.9 s.114
• /
• pp.949-957
• /
• 2006

In this Paper, reduction of noise and vibration in ship cabins by using floating floor is studied. Two theoretical models are presented and predicted insertion losses of floating floor are compared to experimental results, where measurements have been done in mock-up built for simulating typical ship cabin structures. In ships, mineral wool is usually used as the impact absorbing materials. The first model (M-S-Plate Model) is that upper plate and mineral wool are assumed as a one-dimensional mass-spring system, which is in turn attached to the simply supported elastic floor. The second model (Wave-Plate Model) is that mineral wool is assumed as an elastic medium for wave propagation. The comparisons show that M-S-Plate model is in good agreement with experimental results when density of mineral wool is 140K, and fiber direction is horizontal. For higher density and vertical fiber direction, Wave-Plate model shows good agreements with measurements. It is found that including the elastic behavior of the floor is essential in improving accuracy of the prediction for low frequency ranges below $100{sim}200Hz$.

• International Journal of Aeronautical and Space Sciences
• /
• v.11 no.4
• /
• pp.326-337
• /
• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.58 no.2
• /
• pp.53-63
• /
• 2016

Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

• Journal of the Korean Society for Railway
• /
• v.12 no.3
• /
• pp.357-363
• /
• 2009

In this paper, field measurements in the subway tunnel and adjacent building were performed to predict the pound vibration level induced by urban rapid transit (subway) in Seoul, Korea. From the results of the measurements, the measured ground vibration level induced by subway in Seoul is smaller than the empirical formula of New York, but it is bigger than the empirical formula of Tokyo which has been commonly used in Korea. We suggested the empirical formula for prediction of ground vibration level induced by subway in Seoul considering on the wave propagation path for soils or rocks, respectively.

• KEPCO Journal on Electric Power and Energy
• /
• v.2 no.1
• /
• pp.89-96
• /
• 2016

The mechanism for laminar dust flame propagation can only be elucidated from a comprehensive mathematical model which incorporates conduction and radiation, as well as the chemical kinetics of particle devolatilization and gas phase and char reaction. The mathematical model for a flat, laminar, premixed coal-air flame is applied to the atmospheric coal-air mixtures studied by Smoot and co-workers, and comparisons are made with their measurements and predictions. Here the principal parameter for comparison is the laminar burning velocity. The studies of Smoot and co-workers are first reviewed and compared with those predicted by the present model. The effects of inlet temperature and devolatilization rate constants on the burning velocities are studied with the present model, and compared with their measurements and predictions. Their measured burning velocities are approximately predicted with the present model at relatively high coal concentrations, with a somewhat increased inlet temperature. From the comparisons, their model might over-estimate particle temperature and rates of devolatilization. This would enable coal-air mixtures to be burned without any form of preheat and would tend to increase their computed values of burning velocity.