• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.727-731
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• 2000

This paper presents a new practical autopilot design approach to acceleration control for tail-controlled STT(Skid-to-Turn) missiles. The approach is novel in that the proposed parametric affine missile model adopts acceleration as th controlled output and considers the couplings between the forces as well as the moments and control fin deflections. The aerodynamic coefficients in the proposed model are expressed in a closed form with fittable parameters over the whole operating range. The parameters are fitted from aerodynamic coefficient look-up tables by the function approximation technique which is based on the combination of local parametric models through curve fitting using the corresponding influence functions. In this paper in order to employ the results of parametric affine modeling in the autopilot controller design we derived a parametric affine missile model and designed a feedback linearizing controller for the obtained model. Stability analysis for the overall closed loop sys-tem is provided considering the uncertainties arising from approximation errors. the validity of the proposed modeling and control approach is demonstrated through simulations for an STT missile.

• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.2
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• pp.90-100
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• 1994

Ultrasonic velocities are widely used in the investigation of material properties. In this paper, a micromechanics model and the ultrasonic velocity were used to develop a nondestructive method to determine the density variation due to porosity in structural SiC. The micromechanics model developed can consider the pore shape and orientation. The model also takes into account the interaction between pores so that it can be applied to the material with high porosity content. A contact pulse overlap method was used to measure the ultrasonic velocities of porous SiC samples, and there was a linear correlation between the velocity and density (or porosity). Using the model and the measured velocity, the bulk density can be easily calculated. The calculated density was in good agreement with that obtained by Archimedes' method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.1-7
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• 2020

With the increase in cyber attacks, automated IDS using machine learning is being studied. According to recent research, the IDS using the recursive learning model shows high detection performance. However, the simple application of the recursive model may be difficult to reflect the associated session characteristics, as the overlapping session environment may degrade the performance. In this paper, we designed the session management module and applied it to LSTM (Long Short-Term Memory) recursive model. For the experiment, the CSE-CIC-IDS 2018 dataset is used and increased the normal session ratio to reduce the association of mal-session. The results show that the proposed model is able to maintain high detection performance even in the environment where session relevance is difficult to find.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.6
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• pp.544-550
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• 2009

To analyze the threat decision performance of MWR(Missile Warning Radar) give analysis on condition that we decide the effective threat using the POC(Probability of Over Countermeasure)/PUC(Probability of Under Countermeasure). Thus, we execute the simulation using the Monte-Carlo method to analyze effect, but the execution time of simulation took longer than we expected. In this paper, the effect analysis is proposed using the probability model to reduce the execution time of simulation. We present the setting method of parameter for probability model and the effect analysis result of MWR using the simulation. Also, we present the comparison result of simulation execution time for Monte-Carlo and probability model.

• Journal of the Korean Society of Propulsion Engineers
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• v.4 no.3
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• pp.45-54
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• 2000

Ignition transient is a. very rapid process lasting only in the order of 100 milliseconds and therefore it is difficult to measure all relevant ballistic properties. Numerical simulation is thus useful to quantify some of these hard to measure flow and ballistic properties. One-dimensional model was employed to study the effects of aging using simplified aging scenarios for both N-H sustainer and booster motors. Also the effects of newly designed igniter on the ignition of N-H sustainer was simulated. Radiation effects could be significant in terms of energy flux increase to the propellant surface and the energy exchange between the combustion gas itself. One dimension implementation of radiation showed significant effects for rear-mounted igniter. Implementation of radiation effects into 2-D axi-symmetric numerical model was completed and its effects on the N-H sustainer were examined. To have a reliable prediction of computer model on ignition transient, accurate chemical property data on the propellant and igniter gas are required. It was found that such property data on aged N-H motors are not available. Chemical aging model can be used to predict to some degree of accuracy effects of aging on chemical and mechanical properties. Such a model was developed, albeit 2-dimensional, to study migration of moisture through a representative solid rocket motor configuration.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1221-1229
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• 2014

In this paper we choose the best model among several bivariate Poisson models on Korean soccer data. The models considered allow for correlation between the number of goals of two competing teams. We use an R package called bivpois for bivariate Poisson regression models and the data of K-league for season 1983-2012. Finally we conclude that the best fitted model supported by the AIC and BIC is the bivariate Poisson model with constant covariance. The zero and diagonal inflated models did not improve the model fit. The model can be used to examine home-away effect, goodness of fit, attack and defense parameters.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.58-63
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• 2022

Recently, the improvement of computational processing ability due to the rapid development of computing technology has greatly advanced the field of artificial intelligence, and research to apply it in various domains is active. In particular, in the national defense field, attention is paid to intelligent recognition among machine learning techniques, and efforts are being made to develop object identification and monitoring systems using artificial intelligence. To this end, various image processing technologies and object identification algorithms are applied to create a model that can identify friendly and enemy weapon systems and personnel in real-time. In this paper, we conducted image processing and object identification focused on tanks among various weapon systems. We initially conducted processing the tanks' image using a convolutional neural network, a deep learning technique. The feature map was examined and the important characteristics of the tanks crucial for learning were derived. Then, using YOLOv5 Network, a CNN-based object detection network, a model trained by labeling the entire tank and a model trained by labeling only the turret of the tank were created and the results were compared. The model and labeling technique we proposed in this paper can more accurately identify the type of tank and contribute to the intelligent recognition system to be developed in the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.572-579
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• 2022

The analysis of foreign aircraft appearing suddenly in air defense identification zones requires a lot of cost and time. This study aims to develop a pre-trained model that can identify neighboring military aircraft based on aircraft photographs available on the web and present a model that can determine which aircraft corresponds to based on aerial photographs taken by allies. The advantages of this model are to reduce the cost and time required for model classification by proposing a pre-trained model and to improve the performance of the classifier by data augmentation of edge-detected images, cropping, flipping and so on.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.362-371
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• 2022

As considerable interests in noise emission from the ships have been increased, International Maritime Organization (IMO) standardized the Underwater Radiated Noise (URN) measurement process of commercial ships in deep seas by enacting the related ISO standard ISO 17208-1 and classification societies responded with the enactment or revision of corresponding notations. According to this trend, a new hybrid underwater sound propagation model based on underwater sound propagation theories was developed and its accuracy on analysis was verified through the result comparison with the results of other generally used models. Using the verified model, each URN propagation characteristics adjusted by the correction methods proposed in the ISO standard and class notations were analyzed and compared in two assumed URN measurement cases. The results showed that the effects of transmission loss corrections in the circumstances with less bottom reflections generally similar but they had rather large differences in the model analysis results with bottom-reflection-dominant conditions. It was concluded that the deep consideration of effective bottom-reflection-correction method should be made in future revisions of ISO standard and class notations.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.9-15
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• 2023

The task of generating a reduced thermal model of a satellite must be performed at least once in a satellite project to shorten the time of orbital thermal analysis and perform thermal analysis coupled to a launch vehicle. Although there are various methods for generating a reduced thermal model, an intuitive and convenient iso-thermal mesh generation method is used the most widely in practice. However, there is still a lack of research on automation of the isothermal mesh generation method. In this paper, we proposed an automated generation method of satellite reduced thermo-mathematical model based on the isothermal mesh generation method considering temperature tolerance and fixed nodes. The proposed method was validated using three different temperature tolerance cases. The average temperature difference satisfied the guidelines of ECSS.