Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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Range-Doppler Clustering of Radar Data for Detecting Moving Objects

이동물체 탐지를 위한 레이다 데이터의 거리-도플러 클러스터링 기법

  • Kim, Seongjoon (Defense Unmanned Technology Center, Agency for Defense Development) ;
  • Yang, Dongwon (Defense Unmanned Technology Center, Agency for Defense Development) ;
  • Jung, Younghun (Defense Unmanned Technology Center, Agency for Defense Development) ;
  • Kim, Sujin (Defense Unmanned Technology Center, Agency for Defense Development) ;
  • Yoon, Joohong (Defense Unmanned Technology Center, Agency for Defense Development)
  • 김성준 (국방과학연구소 국방무인기술센터) ;
  • 양동원 (국방과학연구소 국방무인기술센터) ;
  • 정영헌 (국방과학연구소 국방무인기술센터) ;
  • 김수진 (국방과학연구소 국방무인기술센터) ;
  • 윤주홍 (국방과학연구소 국방무인기술센터)
  • Received : 2014.05.15
  • Accepted : 2014.11.07
  • Published : 2014.12.05
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Abstract

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance are reported. In near field, several hits per an object are generated after signal processing of Radar data. Hence, clustering is an essential technique to estimate their shapes and positions precisely. This paper proposes a method of grouping hits in range-doppler domains into clusters which represent each object, according to the pre-defined rules. The rules are based on the perceptual cues to separate hits by object. The morphological connectedness between hits and the characteristics of SNR distribution of hits are adopted as the perceptual cues for clustering. In various simulations for the performance assessment, the proposed method yielded more effective performance than other techniques.

Keywords

References

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Cited by

  1. Width Estimation of Stationary Objects using Radar Image for Autonomous Driving of Unmanned Ground Vehicles vol.18, pp.6, 2015, https://doi.org/10.9766/KIMST.2015.18.6.711