• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.139-148
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• 2022

In this paper, we implement a distributed FMCW MIMO radar system to obtain Micro Doppler signatures of target motions. In addition, we also develop federated learning based motion recognition algorithm based on the Micro-Doppler radar signature collected by the implemented FMCW MIMO radar system. Through the experiment, we have verified that the proposed federated learning based algorithm can improve the motion recognition accuracy up to 90%.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.517-522
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• 2023

Existing radars have been developed by applying RF sub-array algorithms, and recently, fully digital Multiple-Input Multiple-Output (MIMO) radar algorithms have been implemented for vehicle radars. In this paper, the radar algorithm applying the Phased MIMO method to the hardware of the RF sub-array method, which is an unsecured technology, was implemented and verified in real time. In order to secure RF sub-array Phased MIMO algorithm technology, a hardware structure for FPGA-based real-time signal processing was presented, and performance was first predicted through design and simulation. Through this, the digital signal of FPGA-based broadband MIMO FMCW radar The processing hardware was developed, and the Phased MIMO radar algorithm of the RF sub-Array method was finally implemented and verified in real time. Based on this, it is judged that it will be possible to secure and apply core technologies necessary for terahertz band radar in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.