• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.11-20
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• 2014

Due to the importance of vehicle detector which plays an essential role in generating real-life traffic information, maintaining detector data quality is preeminent in advanced traffic management and information systems (ATMIS). To this end, agencies periodically conduct performance tests on detectors. Detector evaluation is generally performed by comparing baseline data with corresponding detector data. Here, two important things need to be addressed; one is errors (or uncertainties) included in baseline data and the other is the confidence interval concept to represent evaluation results of sample data to corresponding ones of population. To resolve these problems, a new detector evaluation scheme is introduced and the scheme is applied to individual level detector evaluations of loop, video image, and radar detectors. The purpose of individual level evaluation is to eliminate the balancing (or cancelling-out) effects of over- and under-counts. As a consequence, the proposed scheme is proven to be effectively applied to real-world detector evaluations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.36-54
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• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• Journal of IKEEE
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• v.24 no.1
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• pp.232-237
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• 2020

In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.65-71
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• 2012

An OS-CFAR (Ordered Statistics CFAR) based on a sorting algorithm is useful for automotive radar systems in a multi-target situation. However, while the typical cell-averaging CFAR has low computational complexity, the OS-CFAR has much higher computation effort. In this paper, we design the new OS-CFAR architecture with a low computational effort. In the proposed method, since one time sorting processing is performed for the decision of the CFAR threshold, the whole processing effort can be reduced. When the fast sorting technique is employed, the computing time of the proposed OS-CFAR is always much shorter compared with typical OS-CFAR method regardless of the data size. We also present the processing result of proposed architecture using the real radar data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.12
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• pp.77-84
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• 2004

We design and implement the DSP module for automotive radar using FMCW. The designed parameters are based on 77GHz FMCW radar, and show the resolution of 0.4m and 0.67km/h in distance and velocity, respectively. For detecting multiple targets, we discuss the relationship between fb's and targets. In addition, we show that the detection of multiple targets is very simple when the range of $f_r$ is sufficiently larger than that of $f_b$. In the front of ADC, the 2nd order differentiator is applied for reducing the effects of path-loss so that the ADC bits are reduced to 8 bits. The designed block is simulated in Matlab and implemented with DSP and micro-processor.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.34-44
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• 2016

This study was initiated to evaluate the performance of methodologies to estimate the space mean speed(SMS) using the time mean speed(TMS) which was collected from the vehicle detection system(VDS) in expressways. To this end, the methodologies presented in prior studies were firstly summarized. It is very hard to achieve exact SMSs and TMSs due to mechanical and communication errors in the field. Thus, a microscopic traffic simulation model was utilized to evaluated the performance. As a result, the harmonic mean and volume-distance weighted harmonic mean were close to the SMS in the case in which the TMSs of individual vehicles were used. However, when the 30-second-interval aggregated TMS were used, the volume-distance weighted harmonic mean was outstanding. In this study, a radar detector was installed in the Joongbu expressway to collect the SMS. The trajectory of individual vehicles collected from the detector were used to calculate the SMS, which was compared with the estimates using other methodologies selected in this study. As a result, the volume-distance weighted mean was turned out to be close to the SMS. However, as the congestion becomes severe. the deviation between the two speed becomes bigger.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.11
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• pp.1297-1306
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• 2012

This work presents a 77 GHz radar transmitter for the automotive radar system. An integrated 13 GHz frequency synthesizer fabricated using 130 nm RF CMOS process drives a commercial W-band compound semiconductor monolithic multifunction amplifier(MPA), which includes a frequency multiplier by six to generate 77 GHz transmitting signal. The 13 GHz frequency synthesizer includes a high efficiency injection buffer of 4 dBm output power to drive the MPA. The output power of 77 GHz radar transmitter is higher than 13.99 dBm and the magnitude of the reference spur relative to the carrier is -36.45 dBc. The phase noise is -81 dBc/Hz at 1 MHz offset frequency from the carrier.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.218-232
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• 2022

Researches are underway to use a radar sensor, a sensor used for object recognition in vehicles, for position estimation. In particular, a method of classifying dynamic and static objects using the Doppler velocity, the output from the radar sensor, and calculating ego-motion using only static objects has been researched recently. Also, for the existing dynamic object classification, several methods using RANSAC or robust filtering has been proposed. Still, a classification method with higher performance is needed due to the nature of the position estimation, in which even a single failure causes large effects. Hence, in this paper, we propose a method to improve the classification performance compared to existing methods through tracking and filtering of dynamic objects. Additionally, the method used a GMPHD filter to maximize tracking performance. In effect, the method showed higher performance in terms of classification accuracy compared to existing methods, and especially shows that the failure of the RANSAC could be prevented.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.1-8
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• 2023

Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.9
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• pp.936-943
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• 2013

This work presents the design and measured results of the single channel automotive radar system for 76.5~77 GHz long range FMCW radar applications. The transmitter uses a commercial GaAs monolithic microwave integrated circuit(MMIC) and the receiver uses the down converter designed using 65 nm CMOS process. The output power of the transmitter is 10 dBm. The down converter chip can operate at low LO power as -8 dBm which is easily supplied from the transmitter output using a coupled line coupler. All MMICs are mounted on an aluminum jig which embeds the WR-10 waveguide. A microstrip to waveguide transition is designed to feed the embedded waveguide and finally high gain horn antennas. The overall size of the fabricated radar system is $80mm{\times}61mm{\times}21mm$. The radar system achieved an output power of 10 dBm, phase noise of -94 dBc/Hz at 1 MHz offset and a conversion gain of 12 dB.