The Journal of Korean Institute of Information Technology (한국정보기술학회논문지)

Korean Institute of Information Technology (한국정보기술학회)
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Real-time Moving Object Detection Based on RPCA via GD for FMCW Radar

  • Nguyen, Huy Toan (Dept. of Electronics and Computer Eng. Chonnam National University) ;
  • Yu, Gwang Hyun (Dept. of Electronics and Computer Eng. Chonnam National University) ;
  • Na, Seung You (Dept. of Electronics and Computer Eng. Chonnam National University) ;
  • Kim, Jin Young (Dept. of Electronics and Computer Eng. Chonnam National University) ;
  • Seo, Kyung Sik (Dept. of Electronics and Computer Eng. Chonnam National University)
  • Received : 2019.02.25
  • Accepted : 2019.06.21
  • Published : 2019.06.30
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Abstract

Moving-target detection using frequency-modulated continuous-wave (FMCW) radar systems has recently attracted attention. Detection tasks are more challenging with noise resulting from signals reflected from strong static objects or small moving objects(clutter) within radar range. Robust Principal Component Analysis (RPCA) approach for FMCW radar to detect moving objects in noisy environments is employed in this paper. In detail, compensation and calibration are first applied to raw input signals. Then, RPCA via Gradient Descents (RPCA-GD) is adopted to model the low-rank noisy background. A novel update algorithm for RPCA is proposed to reduce the computation cost. Finally, moving-targets are localized using an Automatic Multiscale-based Peak Detection (AMPD) method. All processing steps are based on a sliding window approach. The proposed scheme shows impressive results in both processing time and accuracy in comparison to other RPCA-based approaches on various experimental scenarios.

주파수변조연속파형(FMCW) 레이더 시스템을 사용하는 이동 객체탐지가 최근 각광을 받고 있다. 레이더 객체탐지는 탐지범위 내 존재하는 고정된 객체 및 클러터들로부터 반사되는 잡음신호로 인해 매우 도전적인 문제이다. 본 논문에서는 FCMW 레이다를 이용하여 잡음배경하 이동객체탐지를 위해 강인한 주성분분석법(RPCA)을 이용한다. 먼저 원 레이더 입력신호에 보상과 보정을 적용한다. 다음 경사하강법을 사용하는 RPCA가 저계수의 성질을 갖는 잡음배경 모델을 구하기 위해 사용된다. 본 논문에서는 RPCA 계산을 위해 소요계산량이 적은 새로운 업데이트 알고리즘을 제안한다. 마지막으로 이동객체는 자동 다중스케일에 기반한 피크 탐지법에 의해 정위한다. 모든 단계는 슬라이딩 윈도우 방법 기반하여 처리된다. 제안된 방법을 타 RPCA 기반의 방법들과 다양한 실험 시나리오 상에서 비교했을 때, 처리 속도와 정확도 척도에서 우수한 결과를 보였다.

Keywords

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