• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.254-262
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• 2016

With the increased demand for automotive radar systems, mutual interference between vehicles has become a crucial issue that must be resolved to ensure better automotive safety. Mutual interference between frequency modulated continuous waveform (FMCW) radar system appears in the form of increased noise levels in the frequency domain and results in a failure to separate the target object from interferers. The traditional fast fourier transform (FFT) algorithm, which is used to estimate the beat frequency, is vulnerable in interference-limited automotive radar environments. In order to overcome this drawback, we propose a high-resolution frequency estimation technique for use in interference environments. To verify the performance of the proposed algorithms, a 77GHz FMCW radar system is considered. The proposed method employs a high-resolution algorithm, specially the multiple signal classification and estimation of signal parameters via rotational invariance techniques, which are able to estimate beat frequency accurately.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.555-560
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• 2009

A vehicle radar has been studied to avoid the collision of vehicles. A vehicle radar using direct sequence-ultra wideband (DS-UWB) measures the distance between a vehicle and an objective with a sufficient time margin. Therefore, the receiver should estimate the distance by processing the short UWB pulse rapidly. There have been several investigations for distance measuring based on DS-UWB signals. In this paper, we propose a novel method for rapid measuring processing time. Simulation results show that the proposed method has a shorter processing time than the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2628-2635
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• 2010

This paper analyzes the detection probability of FMCW (Frequency Modulated Continuous Wave) radar based on Doppler frequency and analog-digital converter bit and designs and implements signal processing part of FMCW radar. For performance evaluation, the FMCW radar system consists of a transmitted part and a received part and uses AWGN channel. The system model is verified through analysis and simulation. Frequency offset occurs in the received part caused by the mismatching between the received signal and the reference signal. In case of Doppler frequency less than about 38KHz, performance degradation of detection does not occur in FMCW radar with 75cm resolution The analog-digital converter needs at least 6 bit in order not to degrade the detection probability. And, we design and implement digital signal processing part based on DDS chip of digital transmitted signal generator for FMCW radar.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.105-115
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• 2017

Conventional traffic detection sensors such as loop detectors and image sensors are expensive to install and maintain and require different detection algorithms depending on the night and day and have a disadvantage that the detection rate varies widely depending on the weather. On the other hand, the millimeter-wave radar is not affected by bad weather and can obtain constant detection performance regardless of day or night. In addition, there is no need for blocking trafficl for installation and maintenance, and multiple vehicles can be detected at the same time. In this study, a multi-target detection algorithm for a radar sensor with this advantage was devised / implemented by applying a conventional single target detection algorithm. We performed the evaluation and the meaningful results were obtained.

• The Magazine of the IEIE
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• v.37 no.5
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• pp.72-83
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• 2010

• The Magazine of the IEIE
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• v.40 no.6
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• pp.28-38
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• 2013

• The Magazine of the IEIE
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• v.41 no.1
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• pp.53-59
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• 2014

• The Magazine of the IEIE
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• v.43 no.10
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• pp.55-60
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• 2016

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.87-95
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• 2020

Purpose: In this paper, we propose an algorithm for detecting respiratory rate and heart beat of a driver of car by exploiting Doppler radar, and verifying the feasibility of the study through experiments. Method: In this paper, we propose a weighted peak detection technique using peak frequency values. The tests are performed in stop-state and driving-state, and the experiment result is analyzed by two proposed algorithms. Result: The results showed more than 95% and 96% accuracy of respiratory and heart rate, respectively. It also showed more than 72% and 84% accuracy of those even for driving experiments. Conclusion: The proposed detection scheme for vital signs can be used for the safety of the driver as well as for prevention of a large size of car accidents.