• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.818-821
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• 2010

본 논문에서는 차량 레이더 시스템용 시그마-델타 변조기를 제안한다. 개발된 변조기는 차량 레이더 시스템에서 고주파 대역 신호의 고해상도 데이터 변환, 즉 아날로그-디지털변환을 수행하는데 사용되며 저전압 및 저 왜곡 특성을 가진 몸체효과 보상형 스위치 구조로 구현되어 있다. 제안된 변조기는 0.25 마이크론 이중 폴리 3-금속 표준 CMOS 공정으로 제작되었고, $1.9{\times}1.5mm^2$의 다이 면적을 점유한다. 제안된 회로는 2.7V의 동작 전압에서 기존의 부트스트랩형 회로보다 약 20dB 향상된 우수한 총 고조파 왜곡 특성을 보였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.771-773
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• 2014

본 논문에서는 장거리 레이더용 차량 충돌 방지 77-GHz CMOS 믹서를 제안한다. 이러한 회로는 2볼트 전원전압에서 동작하며, 저 전압 전원 공급에서도 높은 변환 이득과 낮은 변환 손실 및 낮은 잡음지수를 가지도록 설계되어 있다. 제안한 회로는 TSMC $0.13{\mu}m$ 혼성신호/고주파 CMOS 공정($f_T/f_{MAX}=120/140GHz$)으로 설계하였다. 전체 칩 면적을 줄이기 위해 수동형 인덕터 대신 전송선(Transmission Line) 을 이용하였다. 본 논문에서 설계한 믹서는 약 5.2dB의 우수한 변환이득 특성과 2.1dBm의 우수한 IIP3 특성을 보였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.855-857
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• 2014

본 논문에서는 24GHz/77GHz 차량용 거리감지 레이더 센서를 이용하여, 차량 충돌 방지 알고리즘을 제안하고자 한다. 알고리즘은 고주파 거리 감지센서에서 측정된 전압을 이용하여, 전후좌우의 차량의 접근 정보를 획득하고 이를 효율적으로 이용하여, 여러 가지 상황에 따른 차량충돌방지를 할 수 있도록 설계되어 있다. 제안된 차량방지 알고리즘은 현재 운행 중인 속도를 기반으로 속도구간별 운행정보를 계산하여 충돌방지를 위한 알고리즘을 설계하였다. 본 연구에서 설계한 차량충돌방지 알고리즘은 차량 주행에서 좌우 차량충돌 없이 효율적으로 운행을 하는 특성을 보였다.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.37-68
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• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.330-333
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• 2016

In this paper, we propose 77 GHz power amplifier for long range automotive collision avoidance radar using 65 nm CMOS process. The proposed circuit has a 3-stage single power amplifier which includes common source structure and transformer. The measurement results show 18.7 dB maximum voltage gain at 13 GHz 3 dB bandwidth. The measured maximum output power is 10.2 dBm, input $P_{1dB}$ is -12 dBm, output $P_{1dB}$ is 5.7 dBm, and maximum power add efficiency is 7.2 %. The power amplifier consumes 140.4 mW DC power from 1.2 V supply voltage.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.10
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• pp.941-944
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• 2016

This paper proposes 24 GHz power amplifier for automotive collision avoidance and surveillance short range radar using Samsung 65-nm CMOS process. The proposed circuit has a 2-stage differential power amplifier which includes common source structure and transformer for single to differential conversion, impedance matching, and power combining. The measurement results show 15.5 dB maximum voltage gain and 3.6 GHz 3 dB bandwidth. The measured maximum output power is 13.1 dBm, input $P1_{dB}$ is -4.72 dBm, output $P1_{dB}$ is 9.78 dBm, and maximum power efficiency is 17.7 %. The power amplifier consumes 74 mW DC power from 1.2 V supply voltage.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.217-228
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• 2024

LiDAR(Light Detection And Ranging) sensors, which play a pivotal role among cameras, RADAR(RAdio Detection And Ranging), and ultrasonic sensors for the safe operation of autonomous vehicles, can recognize and detect objects in 360 degrees. However, since LiDAR sensors use lasers to measure distance, they are vulnerable to attackers and face various security threats. In this paper, we examine several security threats against LiDAR sensors: relay, spoofing, and replay attacks, analyze the possibility and impact of physical jamming attacks, and analyze the risk these attacks pose to the reliability of autonomous driving systems. Through experiments, we show that jamming attacks can cause errors in the ranging ability of LiDAR sensors. With vehicle-to-vehicle (V2V) communication, multi-sensor fusion under development and LiDAR anomaly data detection, this work aims to provide a basic direction for countermeasures against these threats enhancing the security of autonomous vehicles, and verify the practical applicability and effectiveness of the proposed countermeasures in future research.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.94-104
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• 2000

The accuracy and reliability of the target tracking is very critical issue in the design of automotive collision warning radar A significant problem in multi-target tracking (MTT) is the target-to-measurement data association If an incorrect measurement is associated with a target, the target could diverge the track and be prematurely terminated or cause other targets to also diverge the track. Most methods for target-to-measurement data association tend to coalesce neighboring targets Therefore, many algorithms have been developed to solve this data association problem. In this paper, a new multi-target data association method based on order statistics is described The new approaches. called the order statistics probabilistic data association (OSPDA) and the order statistics joint probabilistic data association (OSJPDA), are formulated using the association probabilities of the probabilistic data association (PDA) and the joint probabilistic data association (JPDA) filters, respectively Using the decision logic. an optimal or near optimal target-to-measurement data association is made A computer simulation of the proposed method in a heavy cluttered condition is given, including a comparison With the nearest-neighbor CNN). the PDA, and the JPDA filters, Simulation results show that the performances of the OSPDA filter and the OSJPDA filter are superior to those of the PDA filter and the JPDA filter in terms of tracking accuracy about 18% and 19%, respectively In addition, the proposed method is implemented using a developed digital signal processing (DSP) board which can be interfaced with the engine control unit (ECU) of car engine and with the d?xer through the controller area network (CAN)

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.11
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• pp.1070-1077
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• 2011

This paper introduces a radar signal processing technique for intelligent rear view monitoring of an automobile. The linear frequency modulation-frequency shift keying(LFM-FSK) waveform, which is the combination of frequency modulation continuous wave(FMCW) and frequency shift keying(FSK) waveform, is employed to simultaneously estimate the range, relative aspect angle, and velocity of an automobile. Hence, it can be applied to monitor the rear view of an automobile. FMCW waveform has high range resolution capability, but it produces ghost targets under a multiple target environment. In contrast, FSK waveform can provide high velocity resolution and avoids the problem of ghost targets. However, it fails to identify multiple targets along the radar's line of sight. With LFM-FSK waveform, we can estimate the ranges and velocities of multiple targets with very high resolution, which avoids the ghost target problem of an FMCW waveform. Simulation result shows that LFM-FSK wavefrom is suitable for use in the lane change assistance system for an automobile.