• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.2
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• pp.218-225
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• 2015

Inverse synthetic aperture radar(ISAR) is coherent imaging system formed by conducting signal processing of received data which consists of radar cross section(RCS) reflected from maneuvering target. A novel algorithm is proposed to compensate inter-pulse motion(IPM) for the purpose of forming an well-focused ISAR image through signals generated by stepped chirp waveform( SCW). The velocity and acceleration of the target related to IPM are estimated based on particle swarm optimization (PSO) which has been widely used in optimization technique. Furthermore, a modified PSO which enables us to improve the performance of PSO is used to compensate IPM in a very short-time. Simulation results using point scatterer model of a Boeing-737 aircraft validate the performance of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1231-1237
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• 2014

It is essential to perform driving performance tests of military vehicles on rough terrain. A full car test is limited by cost and time constraints, because of which a dynamic analysis via computer simulation is preferred. In this study, a vehicle model is developed using MSC.ADAMS, a commercial multibody analysis program, and compared via experiments. FTire is modeled using the results of a tire performance test to obtain the vertical stiffness. A nonlinear damper is modeled by a characteristic experiment. Leaf springs are modeled with beam force elements and consisted to a vehicle model. The vertical force and acceleration response of the wheel are identified when vehicle is passing over a simple bump as well as a sinusoidal road. The developed vehicle model is verified with the results of a full car test.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.487-495
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• 2018

Experimental analysis of the spray characteristics of the movable sleeve injector, which can simultaneously control the area of the annular gap and the pintle gap, has been studied and a method for controlling the uniform performance over a wide thrust range has been studied. It is confirmed that the design flow rate is not satisfied when the constant pressure difference is set regardless of the opening distance of the sleeve. In order to improve this, the differential pressure in the annular gap and the pintle gap was applied differently according to the opening distance. It was confirmed that the design flow rate was satisfied within the operating range and thrust control was linear from 25% to 100% in linear sleeve area.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.71-81
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• 1995

In this paper, feature vector extraction methods and classification algorithms for the automatic classification of transient signals in underwater are discussed. A feature vector extraction method using wavelet transform, which shows good performance with small number of coefficients, is proposed and compared with the existing classical methods. For the automatic classification, artificial neural networks such as multilayer perceptron (MLP), radial basis function (RBF), and MLP-Class are utilized, where those neural networks as well as extracted feature vectors are combined to improve the performance and reliability of the proposed algorithm. It is confirmed by computer simulation with Traco's standard transient data set I and simulated data that the proposed feature vector extraction method and classification algorithm perform well, assuming that the energy of a given transient signal is sufficiently larger than that of a ambient noise, that there are the finite number of noise sources, and that there does not exist noise sources more than two simultaneously.

• Journal of Korea Multimedia Society
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• v.23 no.5
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• pp.641-649
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• 2020

As the usage of mobile devices extremely increases, malicious mobile apps(applications) that target mobile users are also increasing. It is challenging to detect these malicious apps using traditional malware detection techniques due to intelligence of today's attack mechanisms. Deep learning (DL) is an alternative technique of traditional signature and rule-based anomaly detection techniques and thus have actively been used in numerous recent studies on malware detection. In order to develop DL-based defense mechanisms against intelligent malicious apps, feeding recent datasets into DL models is important. In this paper, we develop a DL-based model for detecting intelligent malicious apps using KU-CISC 2018-Android, the most up-to-date dataset consisting of benign and malicious Android apps. This dataset has hardly been addressed in other studies so far. We extract OPcode sequences from the Android apps and preprocess the OPcode sequences using an N-gram model. We then feed the preprocessed data into LSTM and apply the concept of Information Gain to improve performance of detecting malicious apps. Furthermore, we evaluate our model with numerous scenarios in order to verify the model's design and performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.2
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• pp.141-149
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• 2018

This paper presents a neural network controller design for complex damage to a blended wing Unmanned Aerial Vehicle(UAV): partial loss of main wing and vertical tail. Longitudinal/lateral axis instability and the change of flight dynamics is investigated via numerical simulation. Based on this, neural network based adaptive controller combined with two types of feedback linearization are designed in order to compensate for the complex damage. Performance of two kinds of dynamic inversion controllers is analyzed against complex damage. According to the structure of the dynamic inversion controller, the performance difference is confirmed in normal situation and under damaged situation. Numerical simulation verifies that the instability from the complex damage of the UAV can be stabilized via the proposed adaptive controller.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.148-156
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• 2013

Since the demand for new military vehicle to fulfill the necessary conditions such as multi-purpose, high-mobility, and survivability has raised continuously from the army, the prototype of a Korean light tactical vehicle was developed to meet these requirements using our own technology. In particular, the new tactical vehicle was equipped with a double wishbone independent suspension to improve ride and handling and maximize off-road driving performance. In this paper, a comprehensive virtual durability process to evaluate the service life of the prototype is presented. A reliability of the trimmed body model based on CATIA data was verified by comparison result between mode analysis and modal test. The dynamic model was constructed using ADAMS/Car, and then the weight distribution and lateral slope driving performance of it were compared with the results of static weight and lateral slope tests. The validity of the VTL(Virtual Test Lab) was checked with test results from the 3-inch spaced impact road. The durability performances of trimmed body and suspension components were evaluated through MSM(Modal Superposition Method) fatigue analysis. It is shown that the virtual durability process could be a helpful tool to find out the weak areas and improve their structures in developing new military vehicle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.221-228
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• 2020

A sonobuoy is dropped onto the surface of water to estimate the bearing of an underwater target. A Directional Frequency Analysis and Recording (DIFAR) sonobuoy has an error in the specific angular section due to the method of estimating bearing and noise, which causes an error in target localization using multiple sonobuoys. In addition, the position of the sonobuoy continues to move, but since a sonobuoy with a GPS is intermittently arranged, it is difficult to estimate the exact position of the sonobuoy. This also causes target localization performance degradation. In this paper, we propose a technique to improve the target localization performance by compensating for bearing errors using characteristics of the DIFAR sonobuoy and multiple-sonobuoy position errors based on the intermittently arranged active sonobuoy with a GPS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.326-333
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• 2015

A turbo fan engine performance analysis program combined with a particle swarm optimization(PSO) has been developed to optimize the major design parameters of the combat aircraft gas turbine engine. The optimized parameters includes bypass ratio, fan pressure ratio, high pressure compression ratio and burner exit temperature. The objective parameters have been determined using a multi-objective function consisting of the net thrust and specific fuel consumption along a weight function. The basic model for the combat aircraft gas turbine engine has been selected as the F404 turbofan engine which is widely used in the combat aircraft, F-18 and Korean high level training aircraft, T-50. The optimal conditions of four parameters have been obtained for various design conditions.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.2
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• pp.290-299
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• 2017

Reconfigurable flight control using various kinds of adaptive control methods has been studied since the 1970s to enhance the survivability of aircraft in case of severe in-flight failure. Early studies were mainly focused on the failure of actuators. Recently, studies of reconfigurable flight controls that can accommodate complex damage (partial wing and tail loss) in conventional aircraft were reported. However, the partial wing loss effects on the aerodynamics of conventional type aircraft are quite different to those of BWB(blended wing body) aircraft. In this paper, a reconfigurable flight control algorithm was designed using a direct model reference adaptive method to overcome the instability caused by a complex damage of a BWB aircraft. A model reference adaptive control was incorporated into the inner loop rate control system enhancing the performance of the baseline control to cope with abrupt loss of stability. Gains of the model reference adaptive control were polled out using the Liapunov's stability theorem. Outer loop attitude autopilot was designed to manage roll and pitch of the BWB UAV as well. A 6-DOF dynamic model was built-up, where the normal flight can be made to switch to the damaged state abruptly reflecting the possible real flight situation. 22% of right wing loss as well as 25% loss for both vertical tail and rudder control surface were considered in this study. Static aerodynamic coefficients were obtained via wind tunnel test. Numerical simulations were conducted to demonstrate the performance of the reconfigurable flight control system.