• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.31-39
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• 2014

Recently, as Intelligent Transportation System (ITS) and self-driving system become influential in the ground transportation system, automotive radar systems have been actively studied among the various radar systems to implement the vehicle collision detection system and distance measurement system between vehicles. Most of the automotive radars are Frequency Modulated Continuous Wave (FMCW) radar type which can calculate distance and velocity of target by estimating the frequency difference between the transmitted signal and received signal. Therefore, accurate frequency estimation is very important in the FMCW radar system. For this reason, to improve the measurement accuracy of the FMCW radar, Reverse Directional FRI (RD-FRI) Super-Resolution technique which has high frequency estimation accuracy is applied to the FMCW radar system. The feasibility of the proposed technique is evaluated with simulation results and compared with FFT and conventional Super-Resolution techniques. The simulation results show that the proposed technique estimates the frequency with high accuracy and the distance with centimeter accuracy.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.134-141
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• 2019

Radar systems are divided into the pulse Doppler (PD) radar and the frequency modulated continuous wave (FMCW) radar depending on the transmission waveform. In particular, the PD radar is advantageous for long-range target detection, and the FMCW radar is suitable for short-range target detection. In this paper, we present design and implementation results for a multi-mode radar signal processor (RSP) that can support both PD and FMCW radar systems to detect unmanned aerial vehicles (UAVs) at short distances as well as long distances. The proposed radar signal processor can be implemented based on Altera Cyclone-IV FPGA with 19,623 logic elements, 9,759 registers, and 25,190,400 memory bits. The logic elements and registers of the proposed radar signal processor are reduced by approximately 43% and 30%, respectively, compared to the sum of logic elements and registers of the conventional PD radar and FMCW radar signal processor.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.25-30
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• 2014

In this paper, we have implemented an FMCW radar for a near distance measurement. In the structure of the FMCW radar, it is a key problem to solve the VCO nonlinearity. In this work, we have adopted a VCO nonlinearity compensation algorithm using the spectrum correlation of beat signals. The radar experimented in this work uses an X-band(9.55~10.25GHz) microwave signal, and realizes precision of 3% in the range of 30m. The prototype can be applied to the front surveillance radar such as in vehicle anti-collision and probing robot mission.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.45-56
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• 2022

The Ieodo Ocean Research Station (IORS) lies between the exclusive economic zone (EEZ) boundaries of Korea, Japan, and China. The geographical positioning of the IORS makes it ideal for monitoring ships in the area. In this study, we introduce ship monitoring results by Automatic Identification System (AIS) and the Broadband 3G^TM radar, which has been developed for use in small ships using the Frequency Modulated Continuous Wave (FMCW) technique. AIS and FMCW radar data were collected at IORS from November 23th to 30th, 2013. The acquired FMCW radar data was converted to 2-D binary image format over pre-processing, including the internal and external noise filtering. The ship positions detected by FMCW radar images were passed into a tracking algorithm. We then compared the detection and tracking results from FMCW radar with AIS information and found that they were relatively well matched. Tracking performance is especially good when ships are across from each other. The results also show good monitoring capability for small fishing ships, even those not equipped with AIS or with a dysfunctional AIS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.86-92
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• 2011

ITS(Intelligent Transport System) has been researched actively to guarantee the smooth traffic and the safety of the vehicle. In recent, as the sensor for the measurement of distance between vehicles, the FMCW radar system in millimeter wave band has been interested in ITS. Actually, 47, 60, 77, 94 and 139 GHz have been assigned for the vehicle radar frequencies in Europe and Japan. However, the performances of the FMCW radar are deteriorated due to the interferences from the surrounding radars and mobile devices. In this paper, in order to model and simulate the performance of FMCW radar under the exterior interference, we propose a new performance parameter, RER(Radius Error Rate), which contains the information of the range error due to the interferences, and show the effectiveness of the proposed parameter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3121-3129
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• 2009

Conventional marine radar systems utilize pulse radar which is capable of high-power transmissions and is effective for remote detection purposes. A pulse radar is most commonly used on medium or large vessels due to its expensive installation and maintenance costs. I propose the use of a Frequency Modulated Continuous Wave (FMCW) radar system operated at low-power and high-resolution instead of the conventional pulse-radar based system. The transmitted and received signals of the FMCW radar system were theoretically analyzed and radar signal processing design and simulation experiments were performed to detect the range and speed. Intermediate Frequency (IF) signal mixed with virtual transmit and receive signals were generated to perform FMCW radar signal processing simulations where the IF signal underwent noise reduction through a lowpass filter. The maximum frequency was derived through the sample interval of the FFT size instead of using A/D converter. This maximum frequency was used to get the frequency range and frequency speed which were in turn used to calculate the range and speed. The virtual beat frequency generated using MATLAB is utilized to analyze the beat frequency used in the actual FMCW radar system signal processing. The differences in the range and speed of the beat frequency signals are processed and analyzed.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.425-428
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• 2001

In this paper, FMCW radar signal processing technique for the vehicle detection system are studied. And FMCW radar sensor is used as a equipment for vehicle detection. To test the performance of developed algorithm, the evaluation of the algorithm is done by simulation for signal processing technique of vehicle detection system. RADAR signal of a driving vehicle is generated by using the Matlab. Distance and velocity of vehicles are calculated with developed a1gorithm. Also the signal processing procedure is done for the virtual data with FM-AM converted noise.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.43-49
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• 2022

FMCW(Frequency Modulated Continuous Wave) Radar is very useful for vehicle collision warning system and autonomous driving sensor. In this paper, the design and implementation of FMCW radar based on two chip MMIC developed as an autonomous driving sensor was described. Especially, generation of frame-based and chirp-based waveform generation and signal processing are mixed to have the strength of maximum detection speed and compensation of speed. This implemented system was analyzed for performance and commercialization potential through lab. test and driving test in K-city.