• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.27-32
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• 2010

77GHz FMCW(Frequency Modulation Continuous Wave) radar system has been used for automotive active safety systems. In typical automotive radar, the moving target detection and clutter cancellation including stationary targets are very important signal processing algorithms. This paper proposed the moving target detection algorithm which improve the detection probability and reduce the false alarm rate. First, the proposed moving target beat-frequency extraction filter is used in order to suppress clutter, and then the data association is applied by using the extracted moving target beat-frequency. Then, the zero-Doppler target is eliminated to remove the rest of clutter.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.554-560
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• 2017

Accurate altimetry is required for the reliable flight control of drones or unmanned air vehicles (UAVs), and the radar altimeter is commonly used owing to its accuracy for the ground level. Due to the limitation for size, weight and power consumption, the frequency modulated continuous wave (FMCW) radar is appropriate for drone because it has lower complexity than that of pulse Doppler (PD) radar. Especially, fast-ramp FMCW radar, which transmits linear FM signal during very short period, is generally utilized, because it is robust for the ego-motion of drone. Therefore, we present the design and implementation results of the radar signal processor (RSP) for fast-ramp FMCW radar system. The proposed RSP was designed with Verilog-HDL and implemented with Altera Cyclone-IV FPGA device. Implementation results show that the proposed RSP includes 27,523 logic elements, 15,798 registers and memory of 138Kbits and can measure the altimeter at the rate of 100Hz with the operating frequency of 50MHz.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.8
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• pp.970-974
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• 2007

A mixer is a key component in the wireless communication systems. In this paper, we design a mixer which is used in a frequency modulated continuous wave(FMCW) radar system. The frequency sweep range of the radar is from 10 GHz to 11 GHz. The transmitted and received signals of the FMCW radar are applied to LO and RF ports of the mixer, respectively, but the frequency difference between the two signals, which is called "a beat frequency" is under a few KHz and depending on the distance to target. Thus the isolation between the LO and RF ports is very important factor to design this mixer. In this paper we propose a single balanced resistive mixer using GaAs MESFET for this application. We first design a single-ended type resistive mixer using a simulation tool, then design a balanced type to increase the LO-to-RF isolation of the mixer. We fabricated the mixer on the substrate of dielectric constant 10 and thickness 0.635 mm. The measured results show that the isolation and conversion loss of the mixer over the frequency band is 20dB and 10.5dB, respectively. The LO input power for operating the proposed mixer is +3dBm, which is lower than a general conventional mixer's LO power. The 1 dB compression point is 6dBm.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.307-314
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• 1999

The potential use of ranging sensors for reducing the occurrence of accidents in real environment is explored by many companies and laboratories. Most of the sensors under investigation utilize the FMCW(Frequency Modulated Continuous Wave) waveforms. The automotive environment presents to the FMCW radar sensor a multitude of moving and fixed targets and the sensor must detect and track only the targets which may pose a threat of collision or passengers accident. The sensor must function accurately in the presence of background echoes generated by moving and fixed targets, ground reflections, atmospheric noises, including rains, fog, and, snow and noise generated within the receiver. False detection of the desired target in this environment may issue false alarms. That may be dangerous to the passenger and the vehicle. A high false alarm rate is totally unacceptable. The false alarm mechanism consists of noise peaks, crossing the threshold and the undesired response of the system to off lane targets which are not potentially hazardous to the radar equipped vehicle. This paper presents an improve technique safety performance for driver-less operation using FMCW radar sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.890-893
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• 2014

In this paper, we present a signal processing algorithm for a marine radar system, in which the evaluation of probability of collision as well as target detection and tracking are performed. Moreover, the digital signal processor that implements the algorithm is proposed. As simulation environment, a mechanically scanning antenna utilizing FMCW signal is used, conducting the beamforming operation with 1 degrees intervals. Test board consists of DSP chips and FPGA, which enable the implemented system to operate in real-time.

• Journal of IKEEE
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• v.28 no.3
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• pp.397-404
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• 2024

This paper presents the design and implementation results of a Raspberry-Pi-based embedded system with an FPGA accelerator that can detect and classify objects using an FMCW radar sensor for preventing door collision accidents in vehicles. The proposed system performs a radar sensor signal processing and a deep learning processing that classifies objects into bicycles, automobiles, and pedestrians. Since the CNN algorithm requires substantial computation and memory, it is not suitable for embedded systems. To address this, we implemented a lightweight deep learning model, BNN, optimized for embedded systems on an FPGA, and verified the results achieving a classification accuracy of 90.33% and an execution time of 20ms.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.253-258
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• 2021

In this paper, we developed a hardware and software platform of the real-time data logging system to verify radar FEM (Front-end Module) and signal-processing algorithms. We developed a hardware platform based on FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) and implemented firmware software to verify the various FEMs. Moreover, we designed PC based software platform to control radar logging parameters and save radar data. The developed platform was verified using 24 GHz multiple channel FMCW (Frequency Modulated Continuous Wave) in an environment of stationary and moving targets of chamber room.

• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.65-71
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• 2023

In this paper, the design, fabrication and verification steps of an electronically scanned array antenna(AESA) for a photonics-based Ku-band FMCW radar system is described. The presented system consists of a transmitter and a receiver respectively, which has a same antenna in the transceiver. The designed antenna has 2×8 array configuration and operates at Ku-band. The VSWR(Voltage Standing Wave Ratio) of each 16-radiators and the coupling power between radiators is measured. Also, in order to minimize the radar system damage because of handover power from the transmitter antenna to the receiver antenna when the transmitter works, the isolation between the transmitter antenna and the receiver antenna is optimized by test. As a result, beamwidth, side lobe level and beam steering characteristic are obtained by synthesizing each radiator pattern measurement data after each beam pattern of 16-radiators is measured in the near-field chamber.

• Journal of IKEEE
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• v.28 no.3
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• pp.296-302
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• 2024

In this paper, we propose a driver condition monitoring system using FMCW in-cabin radar, which is free from wearing inconvenience and privacy issues. Using 77GHz high-precision radar, the system detects changes in eye blinking patterns according to changes in the driving environment and the driver's condition using an adaptive multiple filtering algorithm, and accurately determines drowsy driving by measuring the number of eye blinks and the time it takes to open and close the eyes through the detected data. With the emergence of high-performance radars that are becoming more and more miniaturized, it is possible to embed them in the instrument panel or rearview mirror of the vehicle, and if the driver is judged to be drowsy, it can wake up the driver through an alarm or interlock with the vehicle's driving system to slow down and make an emergency stop to prevent accidents and promote driver safety.