• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.314-320
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• 2016

Inertial navigation system (INS) has used aided systems and sensors to compensate navigation error. Global navigation satellite system (GNSS), velocity measurement sensor (VMS), and radar are commonly used to aid INS. Land navigation system (LNS) also mainly uses VMS when GNSS cannot be used such as at tunnel or on jammed scenario. A straight drive is required when VMS-aided navigation is used, because there is only speed of straight direction whereas no crossways and vertical directions. In local environment, even an expressway has lack of straight drive which is constraint of VMS-aided navigation algorithm. This paper proposes an enhanced VMS-aided navigation algorithm for LNS with indirect drive by restricting filter update condition. Also, there is a result of vehicle test to prove performance of the proposed algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.2
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• pp.121-126
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• 2004

This paper presents an SAR-data calibration technique using a well-calibrated scatterometer. At first a fully-polarimetric antenna pattern(magnitude and phase) of the antenna main-beam using a conducting sphere was measured. Then, this data were used to calibrate polarimetrically an auto-mounted network analyzer-based scatterometer system. This scatterometer system can be used to measure the accurate Mueller matrices of earth surfaces such as grass fields, rice fields and bare soil surfaces; i.e., the phase-difference parameters can be obtained as well as the radar scattering coefficients. If a polarimetrically calibrated scatterometer is operated at the same time with the SAR system, the scatterometer data can be used to correct the SAR data, especially the phase-difference parameters. It was found that the correction effect is remarkable for the degree of correlation ${\alpha}$, which is one of the phase-difference parameter, while the correction effect is negligible for the magnitude parameters(backscattering coefficients).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1271-1280
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• 2012

In the recent parking assistant systems, finding out the distance to the object behind a car is often performed by the range sensors such as ultrasonic sensors, radars. However, the installation of additional sensors on the used vehicle could be difficult and require extra cost. On the other hand, the motion stereo technique that extracts distance information using only an image sensor was also proposed. However, In the stereo rectification step, the motion stereo requires good features and exacts matching result. In this paper, we propose a fast algorithm that extracts the accurate distance information for the parallel parking situation using the consecutive images that is acquired by a rear-view camera. The proposed algorithm uses the quadrangle transform of the image, the horizontal line integral projection, and the blocking-based correlation measurement. In the experiment with the magna parallel test sequence, the result shows that the line-accurate distance measurement with the image sequence from the rear-view camera is possible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.30-44
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• 2022

The advent of deep learning-based algorithms has facilitated researches on target detection from synthetic aperture radar(SAR) imagery. While most of them concentrate on detection tasks for ships with open SAR ship datasets and for aircraft from SAR scenes of airports, there is relatively scarce researches on the detection of SAR ground vehicle targets where several adverse factors such as high false alarm rates, low signal-to-clutter ratios, and multiple targets in close proximity are predicted to degrade the performances. In this paper, a dataset of ground vehicle targets acquired from TerraSAR-X(TSX) satellite SAR images is presented. Then, both detection and instance segmentation are simultaneously carried out on this dataset based on the deep learning-based Mask R-CNN. Finally, this paper shows the future research directions to further improve the performances of detecting the SAR ground vehicle targets.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.517-522
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• 2023

Existing radars have been developed by applying RF sub-array algorithms, and recently, fully digital Multiple-Input Multiple-Output (MIMO) radar algorithms have been implemented for vehicle radars. In this paper, the radar algorithm applying the Phased MIMO method to the hardware of the RF sub-array method, which is an unsecured technology, was implemented and verified in real time. In order to secure RF sub-array Phased MIMO algorithm technology, a hardware structure for FPGA-based real-time signal processing was presented, and performance was first predicted through design and simulation. Through this, the digital signal of FPGA-based broadband MIMO FMCW radar The processing hardware was developed, and the Phased MIMO radar algorithm of the RF sub-Array method was finally implemented and verified in real time. Based on this, it is judged that it will be possible to secure and apply core technologies necessary for terahertz band radar in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.56-66
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• 2023

Safety accidents are increasing, such as changes in groundwater levels due to construction work or natural influences, or ground cave-ins caused by soil runoff from old water supply and sewage pipes. In addition, underground facility management agencies must make efforts to improve the accuracy of underground information through continuous investigation and exploration in accordance with the Special Act on Enhanced Underground Safety Management. Accordingly, in this study, we defined the configuration of equipment and data processing method to collect 3D precise exploration underground facility information and developed 3D underground facility information collection technology to ensure accuracy of underground facilities. As a result of verifying the developed technology, the horizontal accuracy improved by an average of 6cm compared to the existing method, making it possible to acquire 3D underground facility information within the error range of the public survey work regulations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.635-644
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• 2009

Image processing technique in the outdoor environment is very sensitive, and it tends to lose a lot of accuracy when it rapidly changes by outdoor environment. Therefore, in order to calculate accurate traffic information using the traffic monitoring system, we must resolve removing shadow in transition time, Distortion by the vehicle headlights at night, noise of rain, snow, and fog, and occlusion. In the research, we developed a system to calibrate the amount of traffic, speed, and time occupancy by using image processing technique in a variety of outdoor environments change. This system were tested under outdoor environments at the Gonjiam test site, which is managed by Korea Institute of Construction Technology (www.kict.re.kr) for testing performance. We evaluated the performance of traffic information, volume counts, speed, and occupancy time, with 4 lanes (2 lanes are upstream and the rests are downstream) from the 16th to 18th December, 2008. The evaluation method performed as based on the standard data is a radar detection compared to calculated data using image processing technique. The System evaluation results showed that the amount of traffic, speed, and time occupancy in period (day, night, sunrise, sunset) are approximately 92-97% accuracy when these data compared to the standard data.

• Journal of IKEEE
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• v.22 no.2
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• pp.408-412
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• 2018

In this paper, a 26GHz variable gain amplifier fabricated using a 40nm CMOS process is studied. In the case of an automobile radar using 79 GHz, it is advantageous in designing and driving to drive down to a low frequency band or to use a low frequency band before up conversion rather than designing and matching the entire circuit to 79 GHz in terms of frequency characteristics. In the case of a Phased Array System that uses time delay through TTD (True Time Delay) in practice, down conversion to a lower frequency is advantageous in realizing a real time delay and reducing errors. For a VGA (Variable Gain Amplifier) operating in the 26GHz frequency band that is 1/3 of the frequency of 79GHz, VDD : 1V, Bias 0.95V, S11 is designed to be <-9.8dB (Mea. High gain mode) and S22 < (Mea. high gain mode), Gain: 2.69dB (Mea. high gain mode), and P1dB: -15 dBm (Mea. high gain mode). In low gain mode, S11 is <-3.3dB (Mea. Low gain mode), S22 <-8.6dB (Mea. low gain mode), Gain: 0dB (Mea. low gain mode), P1dB: -21dBm (Mea. Low gain mode).