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구분 SCI
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학술대회 Azimuth Angle Resolution Improvement Technique with Neural Network
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저자
김형주, 유성진, 정병장, 변우진
발행일
202010
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.1384-1387
DOI
https://dx.doi.org/10.1109/ICTC49870.2020.9289364
협약과제
20ZH1100, 연결의 한계를 극복하는 초연결 입체통신 기술 연구, 변우진
초록
This paper introduces a method to improve the azimuth angle resolution using MIMO-FMCW radar. When using a MIMO-FMCW radar, a 2D radar image composed of a range axis and an azimuth axis can be obtained. The range resolution is determined by the bandwidth, and the azimuth resolution is determined by the length of the virtual antenna array and the number of virtual antenna elements. To improve the azimuth angle resolution while avoiding aliasing, in this paper, the virtual antenna was placed wider with non-uniform spacing. Then, deep learning technique was applied to reduce the side lobe effect. The proposed method was verified through experiments using simulation signals and emulation signals based on measurements.
키워드
automotive radar, azimuth angle resolution, deep learning, MIMO-FMCW radar, neural network
KSP 제안 키워드
Angle resolution, Automotive radar, Azimuth Angle, Azimuth resolution, Neural networks, Non-uniform, Radar image, Range resolution, Resolution improvement, Virtual Antenna Array, antenna elements