Analysis of Signal Integrity for High Precision Digital-to-Analog Conversion Circuit

Jing Dai,Yanmei Wang 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.5

In order to improve the accuracy of the digital to analog conversion (DAC), the reflection and crosstalk problems of the signal transmission process were studied in this paper. The Hyperlynx software was used for the simulation study of reflection and crosstalk problems of the master clock signal in the DAC circuit. Source end cascading termination resistor and remote end termination resistor and capacitor (RC) methods were adopted to weaken the reflected signal. The problem of signal crosstalk was solved by the remote end cascading termination resistor method. The experiments results showed that the reflection peak could be eliminated when the value of the source end cascading termination resistor was 100Ω. The reflection peak could be eliminated when the value of remote end termination resistors was 100Ω and the capacitance was 300pF. Terminating 100Ω resistor, shortening the length of the transmission line and decreasing the distance of the adjacent network could weaken crosstalk phenomenon. In high precision digital to analog conversion circuit, the source end cascading termination resistor and the remote RC termination were adopted to solve the problems of signal reflection. The methods of optimizing wiring and the cascading termination resistor weakened the signal crosstalk phenomenon. They also improved signal integrity and ADC accuracy of the signal during transmission.

Measuring displacement signal with an accelerometer

한상보 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.6

An effective and simple way to reconstruct displacement signal from a measured acceleration signal is proposed in this paper. To reconstruct displacement signal by means of double-integrating the time domain acceleration signal, the Nyquist frequency of the digital sampling of the acceleration signal should be much higher than the highest frequency component of the signal. On the other hand, to reconstruct displacement signal by taking the inverse Fourier transform, the magnitude of the significant frequency components of the Fourier transform of the acceleration signal should be greater than the 6 dB increment line along the frequency axis. With a predetermined resolution in time and frequency domain, determined by the sampling rate to measure and record the original signal, reconstructing high-frequency signals in the time domain and reconstructing low-frequency signals in the frequency domain will produce biased errors. Furthermore, because of the DC components inevitably included in the sampling process, low-frequency components of the signals are overestimated when displacement signals are reconstructed from the Fourier transform of the acceleration signal. The proposed method utilizes curve-fitting around the significant frequency components of the Fourier transform of the acceleration signal before it is inverse-Fourier transformed. Curve-fitting around the dominant frequency components provides much better results than simply ignoring the insignificant frequency components of the signal.

Effects of Traffic Signals with a Countdown Indicator

Joonho Chang,Kihyo Jung 대한인간공학회 2017 大韓人間工學會誌 Vol.36 No.5

Objective: This study examined two traffic signals with a countdown indicator in terms of driver"s reaction time and subjective satisfaction score and their performance was compared with a standard traffic signal in driving simulation. Background: Dilemma zone is created when a traffic light changes at intersections. It often pushes drivers to rush in urgent and premature decision making whether to go or stop and thus induces unnecessary mental load among drivers, which may lead to sudden conflicts with following vehicles at intersections. Method: Forty college students (male: 20, female: 20) participated in this driving simulation study. Three traffic signals were employed: (1) standard traffic signal; (2) countdown-separated signal; and (3) countdown-overlaid signal. The countdownseparated and countdown-overlaid signals were designed to inform drivers of the remaining time of a green light before tuning to an amber light. Reaction times (sec) and satisfaction scores (7-point scale) for the two signals with a countdown indicator were compared with those for the standard traffic signal. Results: Reaction times of the countdown-separated (0.49 sec) and countdownoverlaid (0.43 sec) signals were significantly shorter than that of the standard signal (0.67 sec). Satisfaction scores of the countdown-separated (5.3 point) and countdownoverlaid (5.6 point) signals were greater than that of the standard signal (3.8 point). Lastly, the countdown-overlaid signal showed better performance than the countdownseparated signal, but their differences in reaction time (0.06 sec) and satisfaction score (0.3 point) were small. Conclusion: Traffic signals with a countdown indicator can improve drivers" reaction time and satisfaction score than the standard traffic signal. Application: Traffic signals with a countdown indicator will be useful for reducing the length of dilemma zone at intersections, by allowing drivers to predict the remaining time of a green light.

SMART SIGNAL: Smartest Model of Road Traffic SIGNAL

Youngje, Jeong,Gyehyeong, Ahn,Gwangyong, Ko,Eunjin, Choi 한국도로학회 2018 한국도로학회 학술대회 발표논문 초록집 Vol.2018 No.05

In this study, we are developing next-generation traffic signal control system, SMART SIGNAL, which is operated using a traffic big-data. To improve urban’s chronic recurrent congestion, SMART SIGNAL conducts real-time traffic signal control based on travel time data of traffic information systems. This research project started in 2015 and is scheduled to end in 2019. This research project consists of three sub-tasks, which are traffic big-data bank system, signal operation algorithm, and field test for SMART SIGNAL. The traffic big-data bank system includes the travel time and traffic volume data from public and private sector’s traffic information systems. Additionally, this system contains taxi trajectory data, CCTV image and smartphone based traffic data. This big-data system predicts the travel time and traffic volume by intersection movement for real-time signal control. The smart signal operation algorithm of SMART SIGNAL consists three sub-algorithm of PRE-CON, CAERUS, and NIMOS. PRE-CON makes today’s signal timing plan using historical traffic data. CAERUS is traffic responsive signal control algorithm based on predicted travel time. NIMOS is spillback control algorithm for oversaturated condition. In this project, field experiment is planned in 2019 in Seoul.

교차로 우회전 차량 보조등 개선

이남수,김유찬,임준범,김영찬 대한교통학회 2015 대한교통학회지 Vol.33 No.5

본 연구의 목적은 우회전 교통처리를 위한 합리적인 신호운영방법을 제시하는데 있다. 우회전 차량 보조등은 현재 일정한 규정이나 기준없이 다양한 형태로 운영되는 것으로 나타났다. 우회전 차량 보조등을 일관성 없이 사용하고 있고, 전방차량 신호등과 불일치하여 교통사고의 위험이 있다. 우회전 차량 보조등이 적색일 때 우회전이 금지된다는 근거가 부족하며, 법과 다른 의미로 적색점멸신호가 사용되는 문제점이 있는 것으로 분석되었다. 우회전 차량보조등 설치가 신호위반에 미치는 영향을 알아보기 위해 현장 조사를 하였다. 우회전 차량 보조등이 설치된 접근로의 신호위반 비율이 높게 나타나서 우회전 차량 보조등이 우회전시 신호위반 비율을 낮추는 효과는 없는 것으로 분석되었다. 우회전 보조신호등의 유무에 따라 운전자가 신호등 해석에 차이가 있는지에 대한 설문조사를 실시결과, 우회전 보조신호등의 유무나 우회전 보조신호등의 형태에 따라 신호등 해석에는 차이가 없는 것으로 분석되었다. 신호체계변경에 따른 운전자의 혼란을 방지하고, 적신호시 우회전 허용에 따른 교통사고가 심각하지 않음을 고려하여 적신호시 우회전을 전면 금지시키는 것은 신중한 검토가 있어야 할 것으로 판단된다. 적신호시 일시정지후에 다른 차마나 보행자에게 방해가 되지 않는다면 우회전이 가능하도록 도로교통법에 반드시 일시정지할 것을 명시할 필요가 있다. 우회전 보조신호등을 설치하고자 한다면 운전자에게 명확한 신호전달을 위해 화살표 삼색등을 우회전 차량보조등으로 사용하기를 제안하였다. This study aims to suggest a reasonable signal operation method for right-turn traffic management. It was found that the right-turn vehicle supplementary signal is currently operated without clear regulations or criteria. It was also analyzed that right-turn supplementary signals are used without consistency, there is a risk of traffic accidents due to the discordance between supplementary signals and traffic signals of forward vehicles, there is a lack of basis for prohibition of a right turn when right-turn vehicle's supplementary signal is red and the flashing red signal is used in a different sense from the law. In order to see the effect of the installed right-turn vehicle supplementary signals on traffic signal violation, a field investigation was conducted. As the result, there was a high proportion of signal violation on the approach lane with right-turn supplementary signals and this means that right-turn supplementary signals hardly influenced the reduction in proportion of signal violation during a right turn. Additionally, a survey was carried out to see if there were differences in driver's interpretation of traffic signals depending on the installation of right-turn supplementary signals. As the result of the survey, there were no differences in interpretation of traffic signals depending on the installation of right-turn supplementary signals or the types of right-turn supplementary signals. A right turn when the signal was red did not lead to serious traffic accidents, so it is thought that there should be a careful consideration of a total ban on a right turn when the signal is red, in order to prevent driver's confusion due to the change of the signal system. Unless there is a disturbance to cars and pedestrians after a temporary stop when the signal is red, there is a need to specify that vehicles must stop temporarily in the Road Traffic Act to facilitate a right turn. What this study finally suggested is to use tri-colored arrow signals for right-turn car supplementary signals to convey a signal to a driver clearly.

운전자의 방향지시등 사용에 영향을 주는 요인들

홍승권(Seung Kweon Hong),김정식(Jung Sik Kim) 대한인간공학회 2018 大韓人間工學會誌 Vol.37 No.5

Objective: The aim of this study is to investigate several factors that affect the drivers" turn signal light usage. Background: If drivers" use of the turn signals increases, the traffic accident rate can be significantly lowered. Many countries are making a variety of efforts to increase the driver"s use of turn signals. However, studies on factors affecting the use of turn signal lights have not yet been conducted in various ways. Method: Observational study and questionnaire study were conducted together. In the observational study, we observed how the turn signal usage rate varied by six variables; four situations in which the driver should use the turn signal lights, the driving time, the driving location, the driver"s use of the safety seat belt, the driver"s sex and whether or not the vehicle in front of the observed vehicle uses turn signal lights. In the questionnaire study, participants were asked two questions; of the situations in which the driver must use the turn signal lights, the situation with the highest priority and why not using the turn signal lights. Results: As a result of observational study, the usage rate of turn signal light was 67.3%. According to the result of the Chi-square test, the usage rate of the turn signal light was different according to five factors among the six factors. There was no difference in the usage rate of turn signal light according to driver"s sex. The results of the questionnaire study showed that the priority of using turn signal lights was lowest in the situation of lane change and that the most important reason why drivers do not use turn signal lights was that there is no rear vehicle. Conclusion: According to the observational study, drivers" turn signal light usage was variable due to various factors. This may be because many drivers do not use the turn signal lights unconsciously and tend to use the turn signal lights selectively depending on the circumstances. The tendency to use no turn signal in the absence of the following vehicle, as shown in the results of the survey, also mean that drivers do not unconsciously use turn signals. In order to improve the level of traffic safety, it is necessary to increase the factors that have a positive effect on the usage rate of the turn signal lights, and at the same time encourage drivers to use the turn signal lights habitually. Application: The results of this research can be useful in designing a plan to increase the driver"s turn signal light usage rate.

Weak Signal 탐색을 위한 연구개발 환경변화 분석모델 개발

홍성화(Sung-Wha Hong),김유일(You-Eil Kim),배국진(Kuk-Jin Bae),박영욱(Young-Wook Park),박종규(Jong-Kyu Park) 한국기술혁신학회 2009 기술혁신학회지 Vol.12 No.1

본 연구에서는 최근 변화무쌍한 미래 환경에 대처하기 위한 세부적인 환경분석 방법론의 하나로 활발하게 연구되고 있는 weak signal에 대한 탐색 프로세스를 체계화 하고자 하였다. 또한 글로벌 모니터링, 트렌드 분석, 브레인스토밍, 델파이 등의 기법을 토대로 한 정성적 방법과 weak signal tracking board의 개발을 통한 정량적인 방법을 적용하여, 미시적인 환경변화 분석 프로세스(NEST : New & Emerging Signals of Trends)와 이를 적용한 KISTI 이머징 시그널 분석 결과를 제시 하고자 하였다. 구체적으로 환경변화 관련 씨앗 정보를 탐색하기 위한 글로벌 모니터링 체제, weak signal 트래킹 보드를 활용한 약한 신호 분석 단계, study-watch 프레임워크를 토대로 한 up-coming trend 스캐닝 단계, 연구 결과의 객관화를 위한 전문가들의 델파이 평가 단계 등으로 세부 모듈을 설계하였다. 본 프로세스의 결과물인 미래에 큰 변화를 가져올 가능성이 있는 유망기술의 씨앗정보인 weak signal과 새로운 트렌드의 형성 가능 초기조짐정보인 up-coming trend는 우리나라의 차세대 수종 산업(유망기술)을 선정하는 데 활용가능하다. 특히 NEST 프로세스는 소규모 인력으로도 효율성을 발휘할 수 있는 weak signal 탐색 체제로 기술혁신 기업들도 독자적인 NEST 프로세스 개발이 가능할 것이다. The importance of searching the weak signal has been increasingly recognized to cope with rapidly changing circumstances as an environmental analysis technique. This study proposed the NEST process for the searching for the weak signal. The NEST (New & Emerging Signals of Trends) is a micro environmental analysis process based on both quantitative and qualitative method. For this, the weak signal Searching Board is developed and traditional methods as global monitoring, trend analysis, brainstorming and delphi method are implemented to NEST. The NEST process is consists of three stage modules; the global monitoring stage in search of seeds information related to the environmental change, the weak signal analysis stage using the weak signal Tracking Board, and the delphi valuation stage for objectifying the final result. The NEST provides the weak signal of the promising technology which can bring new paradigm and the Up-Coming Trends which can lead new trend in the future. These outputs can be used to select promising technology from firm level to national level. The NEST system can be effectively operated as well as in small group so that small and medium innovative firms can develop and execute their own NEST process individually.

실데이터 기반 능동 소나 신호 합성 방법론

김윤수,김주호,석종원,홍정표 한국음향학회 2024 韓國音響學會誌 Vol.43 No.1

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference –2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

Design and Performance Evaluation of GPS Spoofing Signal Detection Algorithm at RF Spoofing Simulation Environment

임순,임덕원,천세범,허문범,최윤섭,이주현,이상정 사단법인 항법시스템학회 2015 Journal of Positioning, Navigation, and Timing Vol.4 No.4

In this study, an algorithm that detects a spoofing signal for a GPS L1 signal was proposed, and the performance was verified through RF spoofing signal simulation. The proposed algorithm determines the reception of a spoofing signal by detecting a correlation distortion of GPS L1 C/A code caused by the spoofing signal. To detect the correlation distortion, a detection criterion of a spoofing signal was derived from the relationship among the Early, Prompt, and Late tap correlation values of a receiver correlator; and a detection threshold was calculated from the false alarm probability of spoofing signal detection. In this study, an RF spoofing environment was built using the GSS 8000 simulator (Spirent). For the RF spoofing signal generated from the simulator, the RF spoofing environment was verified using the commercial receiver DL-V3 (Novatel Inc.). To verify the performance of the proposed algorithm, the RF signal was stored as IF band data using a USRP signal collector (NI) so that the data could be processed by a CNU software receiver (software defined radio). For the performance of the proposed algorithm, results were obtained using the correlation value of the software receiver, and the performance was verified through the detection of a spoofing signal and the detection time of a spoofing signal.

Retrieving the Time History of Displacement from Measured Acceleration Signal

Han, Sangbo The Korean Society of Mechanical Engineers 2003 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.17 No.2

It is intended to retrieve the time history of displacement from measured acceleration signal. In this study, the word retrieving means reconstructing the time history of original displacement signal from already measured acceleration signal not just extracting various information using relevant signal processing techniques. Unlike extracting required information from the signal, there are not many options to apply to retrieve the time history of displacement signal, once the acceleration signal is measured and recorded with given sampling rate. There are two methods, in general, to convert measured acceleration signal into displacement signal. One is directly integrating the acceleration signal in time domain. The other is dividing the Fourier transformed acceleration signal by the scale factor of - $\omega$$^2$and taking the inverse Fourier transform of it. It turned out both the methods produced a significant amount of errors depending on the sampling resolution in time and frequency domain when digitizing the acceleration signals. A simple and effective way to convert the time history of acceleration signal into the time history of displacement signal without significant errors is studied here with the analysis on the errors involved in the conversion process.