The Journal of Korean Institute of Electromagnetic Engineering and Science (한국전자파학회논문지)

The Korean Institute of Electromagnetic Engineering and Science (한국전자파학회)
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Forward-Looking Synthetic Inverse Scattering Image Formation for a Vehicle with Curved Motion Based on Time Domain Correlation

시간 영역 상관관계 기법을 통한 곡선운동을 하는 차량용 전방 관측 역산란 합성 영상 형성

  • Lee, Hyukjung (School of Electrical Engineering, KAIST) ;
  • Chun, Joohwan (School of Electrical Engineering, KAIST) ;
  • Hwang, Sunghyun (Electronics and Telecommunications Research Institute, ETRI) ;
  • You, Sungjin (Electronics and Telecommunications Research Institute, ETRI) ;
  • Byun, Woojin (Electronics and Telecommunications Research Institute, ETRI)
  • 이혁중 (한국과학기술원 전기 및 전자공학부) ;
  • 전주환 (한국과학기술원 전기 및 전자공학부) ;
  • 황성현 (한국전자통신연구원) ;
  • 유성진 (한국전자통신연구원) ;
  • 변우진 (한국전자통신연구원)
  • Received : 2018.09.21
  • Accepted : 2018.11.05
  • Published : 2019.01.31

Abstract

In this paper, we deal with forward-looking imaging, and focus on forward-looking synthetic inverse scattering imaging for a vehicle with curved motion. For image formation, time domain correlation(TDC) is used and a 2D image of the ground in front of the vehicle is generated. Because TDC is a technique that implements matched filtering for a space-variant system, it is robust to Gaussian additive noise of measurements. Furthermore, comparison and analysis between images from linear motion and curved motion show that the resolution of the image is improved; however, the entropy of the image is increased owing to curved motion.

Keywords

Synthetic Inverse Scattering;Time Domain Correlation;Forward-Looking Imaging;Curved Motion Imaging

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JJPHCH_2019_v30n1_60_f0001.png 이미지

그림 2. 송신하는 선형 주파수 변조 펄스 열 Fig. 2. Transmitting LFM pulse train.

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그림 3. 모의실험 상황 Fig. 3. Simulation scene.

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그림 4. 측정치의 신호 대 잡음 비가 10 dB일 때 차량이 직선운동하는 상황에서 시간 영역 상관관계를 통해 얻은 역산란 합성 영상 Fig. 4. Synthetic inverse scattering image based on TDC when SNR of measurement is 10 dB with linear motion.

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그림 5. 측정치의 신호 대 잡음 비가 10 dB일 때 차량이 곡선운동하는 상황에서 시간 영역 상관관계를 통해 얻은 역산란 합성 영상 Fig. 5. Synthetic inverse scattering image based on TDC when SNR of measurement is 10 dB with curved motion.

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그림 6. 측정치의 신호 대 잡음 비가 10 dB일 때 차량이 곡선운동, 직선운동할 때의 점 분산 함수 비교 Fig. 6. PSF comparison between linear motion and curved motion when SNR of measurement is 10 dB.

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그림 7. 측정치의 신호 대 잡음 비가 0 dB일 때 차량이 직선운동하는 상황에서 시간 영역 상관관계를 통해 얻은 역산란 합성 영상 Fig. 7. Synthetic inverse scattering image based on TDC when SNR of measurement is 0 dB with linear motion.

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그림 8. 측정치의 신호 대 잡음 비가 0 dB일 때 차량이 곡선운동하는 상황에서 시간 영역 상관관계를 통해 얻은 역산란 합성 영상 Fig. 8. Synthetic inverse scattering image based on TDC when SNR of measurement is 0 dB with curved motion.

JJPHCH_2019_v30n1_60_f0008.png 이미지

그림 9. 측정치의 신호 대 잡음 비가 −10 dB일 때 차량이 직선운동하는 상황에서 시간 영역 상관관계를 통해 얻은 역산란 합성 영상 Fig. 9. Synthetic inverse scattering image based on TDC when SNR of measurement is –10 dB with linear motion.

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그림 10. 측정치의 신호 대 잡음 비가 –10 dB일 때 차량이 곡선운동하는 상황에서 시간 영역 상관관계를 통해 얻은 역산란 합성 영상 Fig. 10. Synthetic inverse scattering image based on TDC when SNR of measurement is –10 dB with curved motion.

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그림 1. 차량용 전방 관측 영상레이다의 운용상황 Fig. 1. Forward-looking imaging radar operation geometry with a vehicle.

표 1. 모의실험 파라미터 Table 1. Simulation parameters.

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표 2. 영상의 엔트로피 비교표 Table 2. Comparison of entropy values.

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Acknowledgement

Grant : 자율주행 자동차를 위한 주야/전천후 비디오 SAR 기술 연구

Supported by : 한국전자통신연구원

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