• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1965-1972
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• 2015

The Missile Flight Test Launch Control System is to operate in conjunction with the Fire Control System during flight test to guided weapons. Also, this is a system for the test control and situation monitoring depending on the type of guided weapons and testing purposes. Message structure, communication protocols, such as data types for interworking with the fire control system and the Missile Flight Test Launch Control System are defined in the Launch Control ICD(Interface Control Document). ICD are composed differently of each guided weapons system and each test object. Previously, in order to interwork with the Fire Control System, the interlocking software was developed, which had a variety of problems. Therefore, we developed a new parsing algorithm in order to recognize the variety of Launch Control ICD and verified that the algorithm operates normally by checking transmitting and receiving various message in conjunction with the fire control system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2532-2537
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• 2012

In recent, the researches on driver assistance systems have been actively performed with development of vehicle industry. AVM(Around View Monitoring) Systems, a part of these systems, have been researching and developing. Existing AVM systems have been developed in the forms of embedded systems or a SoC (System on Chip) to provide view around vehicle in real time. However, if Car PC is equipped with in vehicle, AVM can be developed using only software without additional cost. In this study, we implemented AVM system which provides location information by adding the informations such as latitude, longitude and speed to functions of "Car PC" based AVM system. If storing function is added to the AVM system implemented in this study which provides location information, the system with storing function can be used as AVM black box system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.37-48
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• 2005

The efficiency of power supply circuits such as DC-DC converters and batteries varies on the trend of the power consumption because their efficiencies are not fixed. To analyze the efficiency of power supply circuits, we need the temporal behavior of the power consumption of the loads, which is dependent on the activity factors of the devices during the operation. Since it is not easy to model every detail of those factors, one of the most accurate power consumption analyses of power supply circuits is measurement of a real system, which is expensive and time consuming. In this paper, we introduce an active load emulator for embedded systems which is capable of power measurement, logging, replaying and synthesis. We adopt a pattern recognition technique for data compression in that long-term behaviors of power consumption consist of numbers of repetitions of short-term behaviors, and the number of short-term behaviors is generally limited to a small number. We also devise a heterogeneous structure of active load elements so that low-speed, high-current active load elements and high-speed, low-current active load elements may emulate large amount and fast changing power consumption of digital systems. For the performance evaluation of our load emulator, we demonstrate power measurement and emulation of a hard drive. As an application of our load emulator, it is used for the analysis of a DC-DC converter efficiency and for the verification of a low-power frequency scaling policy for a real-time task.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.41-47
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• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.156-165
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• 2006

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-imbedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18$\%$ on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.8
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• pp.685-692
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• 2007

This paper describes the development procedure of GUI Program for the automated generation of airfoil performance table used in helicopter comprehensive code. Considering commercialization, the program is developed based on the Windows operating system. In addition, it is aimed to enhance user's convenience by including embedded postprocessor which enables real-time display of calculation procedure and grid system. Using the validated CFD code, the aerodynamic analyses are automated for a given range of Mach number and angles of attack. The computational grid system is designed to generate automatically once the surface coordinates are given. Mixed-Language scheme is employed in order to combine the CFD code in Fortran with C++ based GUI program, which makes the time-consuming code conversion unnecessary.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.364-366
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• 2017

Unlike general ships, offshore plants require high reliability due to their long operating time at fixed positions when they are operated. Sensor-based status information is required for user and maintenance worker to ensure safety. In this paper, we propose a monitoring system for safety diagnosis and inspection of cargo lift for offshore plant. It consists of a sensor unit mounted on the cargo Lift, an embedded system measurement unit, and a monitoring unit for real-time data verification. It is based on the ship standard network IEC 61162-450 for the exchange of operating information and sensor measurement information in accordance with the upgrading and integration of equipment in maritime.

• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.3
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• pp.118-127
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• 2010

Inter-vehicle communication is one of the most important parts in Intelligent Vehicle System. Through this communication, drivers can recognize what is happening out of their sights, such as the freezing condition of the street, traffic accidents, and so on. Each car in IVS gives various services to the drivers after analyzing those received information from cars or a base station. If the message is, however, exchanged from car to car directly, the computation cost which is needed for all the car to authenticate the transmitted message between nearby cars is tremendously high. Therefore, one can naturally think that the message communication between cars is performed with the help of the base station to reduce the computation cost. In this case where the base station collects all the information transmitted from cars and broadcasts them nearby, there should be an efficient way both for the base station to authenticate the car message within its communication range and for the car to authenticate the information received from the base station. In this paper, we present a two-way authentication protocol using a hash chain to efficiently exchange GPS information between a car and a base station. This information can be used to provide a driver with the navigation which displays all the moving cars around him in real time. When a car goes into an area of a base station, the car authenticates itself to the base station using its private key of PKI, sends a commitment of a hash chain, then starts to send a message with the hash value for authentication. The message includes GPS information, driver's status and so on. The base station also authenticates itself to the nearby cars using its private key, transmits the commitment of the hash chain, and sends all the messages gathered from cars with authentication information.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.86-95
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• 2009

SIFT is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vertices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3D image reconstructions and intelligent vision system for robots. In this paper, we implement a hardware to sift feature detection algorithm for real time processing in embedded systems. We estimate that the hardware implementation give a performance 25ms of $1,280{\times}960$ image and 5ms of $640{\times}480$ image at 100MHz. And the implemented hardware consumes 45,792 LUTs(85%) with Synplify 8.li synthesis tool.