• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.108-117
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• 2003

In this paper, two types of radar vehicle detectors compatible with currently being used ILD(Inductive Loop Detector) without any modification has been developed. With these vehicle detectors based on FMCW altimeter and Doppler speedometer techniques at 24 GHz, the length and speed of a vehicle can be detected. For signal processing part, we have used DAQ board and programmed with LabView. For compatibility with traffic information network connected with existing ILD's, traffic information has been sent to VDS by using RS-232C standard interface. This development has improved approximately 10% in accuracy in terms of the speed and length information compared with that of the installed ILD in the test field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1565-1571
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• 2010

FMCW(Frequency Modulation Continuous Wave) Radar is very useful for vehicle collision warning system because of the simplicity. In this work, a signal processing part of FMCW vehicle radar system is implemented with flexibility using DSP, FPGA, ADC, and DAC so that the system could adopt lots of algorithm and could be improved through road test. It is shown that the system meets basic requirements as designed, and finds some problems in road test. We briefly discuss the problem which are caused by shadow effect from overlapped target and the distortion of beat frequency from the nonlinearity of VCO and the RCS of vehicle.

• Journal of Auto-vehicle Safety Association
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• v.4 no.2
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• pp.32-36
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• 2012

The Automatic unmanned target object carrying system (AUTOCS) is developed for testing road vehicle radar and vision sensor. It is important for the target to reflect the realistic target characteristics when developing ASV or ADAS products. The AUTOCS is developed to move the pedestrian or motorcycle target for desired speed and position. The AUTOCS is designed that only payload target which is a manikin or a motorcycle is detected by the sensor not the AUTOCS itself. In order for the AUTOCS to have low exposure to radar, the AUTOCS is stealthy shaped to have low RCS(Radar Cross Section). For deceiving vision sensor, the AUTOCS has a specially designed pattern on outside skin which resembles the asphalt pattern. The AUTOCS has three driving modes which are remote control, path following and replay. The AUTOCS V.1 is tested to verify the radar detect characteristics, and the AUTOCS successfully demonstrated that it is not detected by a car radar. The result is presented in this paper.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.4
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• pp.514-522
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• 2013

In this paper, we present signal processing procedure and carry out performance analysis of FMCW(Frequency Modulation Continuous Wave) radar for Autonomous Unmanned Vehicle(AUV). In order to detect range profile and velocity of the unknown target, we must implement two step FFT(Fast Fourier Transform) procedure. And the DBF(Digital Beam Forming) algorithm has to be performed to obtain the angle information of the unknown target. To verify the performance of manufactured autonomous unmanned ground vehicle FMCW radar, we use the data of the real corner reflecter target.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.23.5-23
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• 2001

This paper is concerned with the vehicle platooning in the AHS (Automated Highway Systems). For this, a relative navigation system is developed for the vehicles operating as a platoon. The relative navigation system is based on two sensors including GPS and MMWR (Millimeter-Wave Radar) and the federated Kalman Iter processing measurements of them. The architecture of this system requires GPS measurements of a preceding vehicle via communication link. Even if GPS measurements are available, they contain errors which are unacceptably high in vehicle platooning. Therefore, GPS carrier phase is considered. Integer ambiguities of GPS carrier phase measurements are determined by using MMWR ...

• Journal of electromagnetic engineering and science
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• v.19 no.1
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• pp.13-19
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• 2019

This paper proposes a systematic method for estimating detection performances of a frequency-modulated continuous wave radar using electromagnetic simulations. The proposed systematic method includes a radar system simulator that can obtain range-Doppler images using the electromagnetic (EM) simulations in conjunction with a test setup employed for performance evaluation of multiple targets at different velocities in a traffic environment. This method is then applied for optimizing the half-power beamwidths of the antenna array using an evaluation metric defined to improve the detection strengths for the multiple targets. The optimized antenna has vertical and horizontal half-power beam widths of $10^{\circ}$ and $60^{\circ}$, respectively. The results confirm that that the proposed systematic method is suitable to improve the radar detection performance with the enhanced radar-Doppler images.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.265-274
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• 2012

In this paper, we propose a method for preceding vehicle detection and tracking with motion estimation by radar-vision sensor fusion. The motion estimation proposed results in not only correction of inaccurate lateral position error observed on a radar target, but also adaptive detection and tracking of a preceding vehicle by compensating the changes in the geometric relation between the ego-vehicle and the ground due to the driving. Furthermore, the feature-based motion estimation employed to lessen computational burden reduces the number of deployment of the vehicle validation procedure. Experimental results prove that the correction by the proposed motion estimation improves the performance of the vehicle detection and makes the tracking accurate with high temporal consistency under various road conditions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.35-41
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• 2008

The most important requirement for the automotive radars is the simultaneous target range and velocity measurement under environment of multi-target, clutters, multi-path, and so on. If the many vehicles with 77GHz FMCW(Frequency Modulation Continuous Wave) radar system are in the near area we should consider the interference signals occurred by other radar systems because these signals reduce exact detection of range and velocity. In this paper, we propose the interference cancellation method, which each vehicle radar transmits chirp trains with the different frequency sweep shapes. The proposed method is applied into the various applications such as an intelligent vehicle, Robot, and UGV(Unmanned Ground Vehicle).

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).