• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.35D no.9
• /
• pp.1-12
• /
• 1998

We have implemented receiver for a 3 Dimensional Phased-Array Radar detecting the azimuth angle, the altitude, the range of a target on real time. This system consists of high frequency module, which protects receiver and controls sensitivity, intermediate frequency module, monopulse detector, IQ phase detector, AGC controller. A two-channel receiver with same function is implemented for increasing accuracy of target altitude data by amplitude comparison monopulse method. The TSS sensitivity of the receiver is -98dBm. The bandwidth of the receiver is 500 MHz. We can control the system gain manually by 100 dB when be AGC off. The gain and phase unbalance of two channels is 5 dB and 30 degree, respectively. The image rejection rate of the IQ detector is 30 dB. We used duroid substrate and package- type device.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.40 no.10
• /
• pp.45-51
• /
• 2003

In this paper, a scan-based low power BIST (Built-In Self-Test) architecture is proposed. The proposed architecture is based on STUMPS, which uses a LFSR (Linear Feedback Shift Register) as the test generator, a MISR(Multiple Input Shift Register) as the reponse compactor, and SRL(Shift Register Latch) channels as multiple scan paths. In the proposed BIST a degenerate MISR structure is used for every SRL channel; this offers reduced area overheads and has less impact on performance than the STUMPS techniques. The proposed BIST is designed to support both test-per-clock and test-per-scan techniques, and in test-per-scan the total power consumption of the circuit can be reduced dramatically by suppressing the effects of scan data on the circuits. Results of the experiments on ISCAS 89 benchmark circuits show that this architecture is also suitable for detecting path delay faults, when the hamming distance of the data in the SRL channel is considered.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.7
• /
• pp.523-531
• /
• 2018

An analysis technique for detecting moving targets on a single-channel airborne frequency-modulated continuous-wave (FMCW) technology and synthetic aperture radar (SAR) image is presented. To analyze the relative velocities of moving targets, an FMCW-based signal model for stationary and moving targets was studied, and a SAR ambiguity function considering its signal model was simulated. The relative velocities of the moving targets on a reconstructed SAR image can be estimated by peak searching of the SAR ambiguity function, and the stationary and moving targets are easily distinguished when there is a large variation of the relative velocity. Analysis results of the moving targets on a reconstructed FMCW-SAR image, using practical airborne data and a SAR ambiguity process, are compared with the in situ testing in the study area.

• Journal of Advanced Navigation Technology
• /
• v.14 no.4
• /
• pp.553-561
• /
• 2010

This paper proposed the face tracking method which can be effectively applied to the robot's vision system. The proposed algorithm tracks the facial areas after detecting the area of video motion. Movement detection of video images is done by using median filter and erosion and dilation operation as a method for removing noise, after getting the different images using two continual frames. To extract the skin color from the moving area, the color information of sample images is used. The skin color region and the background area are separated by evaluating the similarity by generating membership functions by using MIN-MAX values as fuzzy data. For the face candidate region, the eyes are detected from C channel of color space CMY, and the mouth from Q channel of color space YIQ. The face region is tracked seeking the features of the eyes and the mouth detected from knowledge-base. Experiment includes 1,500 frames of the video images from 10 subjects, 150 frames per subject. The result shows 95.7% of detection rate (the motion areas of 1,435 frames are detected) and 97.6% of good face tracking result (1,401 faces are tracked).

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.5
• /
• pp.168-176
• /
• 2014

Detecting moving objects from a video sequence is a fundamental and critical task in video surveillance, traffic monitoring and analysis, and human detection and tracking. It is very difficult to detect moving objects in a video sequence degraded by the environmental factor such as fog. In particular, the color of an object become similar to the neighbor and it reduces the saturation, thus making it very difficult to distinguish the object from the background. For such a reason, it is shown that the performance and reliability of object detection and tracking are poor in the foggy weather. In this paper, we propose a novel method to improve the performance of object detection, combining a haze removal algorithm and a local histogram-based object tracking method. For the quantitative evaluation of the proposed system, information retrieval measurements, recall and precision, are used to quantify how well the performance is improved before and after the haze removal. As a result, the visibility of the image is enhanced and the performance of objects detection is improved.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4754-4773
• /
• 2018

In sensor medium access control (SMAC) protocol, sensor nodes can only access the channel in the scheduling and listening period. However, this fixed working method may generate data latency and high conflict. To solve those problems, scheduling duty in the original SMAC protocol is divided into multiple small scheduling duties (micro duty MD). By applying different micro-dispersed contention channel, sensor nodes can reduce the collision probability of the data and thereby save energy. Based on the given micro-duty, this paper presents an adaptive duty cycle (DC) and back-off algorithm, aiming at detecting the fixed duty cycle in SMAC protocol. According to the given buffer queue length, sensor nodes dynamically change the duty cycle. In the context of low duty cycle and low flow, fair binary exponential back-off (F-BEB) algorithm is applied to reduce data latency. In the context of high duty cycle and high flow, capture avoidance binary exponential back-off (CA-BEB) algorithm is used to further reduce the conflict probability for saving energy consumption. Based on the above two contexts, we propose an improved SMAC protocol, micro duty adaptive SMAC protocol (MDA-SMAC). Comparing the performance between MDA-SMAC protocol and SMAC protocol on the NS-2 simulation platform, the results show that, MDA-SMAC protocol performs better in terms of energy consumption, latency and effective throughput than SMAC protocol, especially in the condition of more crowded network traffic and more sensor nodes.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.11
• /
• pp.680-688
• /
• 2005

The electrical current generated by heart creates not only electric potential but also a magnetic field. We have observed electrophysiological phenomena of the heart by measuring components of magnetocardiogram(MCG) using 61 channel superconducting quantum interference device(SQUD) system. We have analyzed the possibility and characteristics of MCG parameters for diagnosis of ischemic heart disease. A technique for automatic analysis of MCG signals in time domain was developed. The methods for detecting the position, the interval, the amplitude ratio, and the direction of single current dipole were examined in the MCG wave. The position and interval parameters were obtained by calculating the gradients of a envelope curve which could be formed by the difference between the maximum and minimum envelope of multi-channel MCG signals. We show some differences of the frequency contour map between the normal MCG and the abnormal (ischemic heart disease) MCG. The direction of single current dipole can be defined by rotating the magnetic field according to Biot-Savart's law at each point of MCG signals. In this study, we have examined the direction of single current dipole from searching for the centroids of positive and negative magnetic fields. The amplitude ratio parameters for measuring 57 deviation consisted of A$_{T}$/A$_{R}$ and other ratios. and We developed a new analysis method, which is based on the frequency contour map of electromagnetic field. Using theses parameters, we founded significant differences between normal subjects and ischemic patients in some parameters.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.3
• /
• pp.482-488
• /
• 2009

Mobile Ad-hoc Networks provide communication without a centralized infrastructure, which makes them suitable for communication in disaster areas or when quick deployment is needed. On the other hand, they are susceptible to malicious exploitation and have to face different challenges at different layers due to its open Ad-hoc network structure which lacks previous security measures. Denial of service (DoS) attack is one that interferes with the radio transmission channel causing a jamming attack. In this kind of attack, an attacker emits a signal that interrupts the energy of the packets causing many errors in the packet currently being transmitted. In harsh environments where there is constant traffic, a jamming attack causes serious problems; therefore measures to prevent these types of attacks are required. The objective of this paper is to carry out the simulation of the jamming attack on the nodes and determine the DoS attacks in OPNET so as to obtain better results. We have used effective anomaly detection system to detect the malicious behaviour of the jammer node and analyzed the results that deny channel access by jamming in the mobile Ad-hoc networks.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.3
• /
• pp.159-164
• /
• 2019

Detecting wildfire using only color in image information is a very difficult issue. This paper proposes an algorithm to detect forest fire area by analyzing color and motion of the area in the video including forest fire. The proposed algorithm removes the background region using the Gaussian Mixture based background segmentation algorithm, which does not depend on the lighting conditions. In addition, the RGB channel is changed to an HSV channel to extract flame candidates based on color. The extracted flame candidates judge that it is not a flame if the area moves while labeling and tracking. If the flame candidate areas extracted in this way are in the same position for more than 2 minutes, it is regarded as flame. Experimental results using the implemented algorithm confirmed the validity.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.181-193
• /
• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.