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TBD 처리를 위한 레이더용 파티클 필터 기법 연구

Radar Tracking Using Particle Filter for Track-Before-Detect(TBD)

  • 권지훈 (한화탈레스 레이더.전자전연구소) ;
  • 강성철 (한화탈레스 레이더.전자전연구소) ;
  • 곽노준 (서울대학교 융합과학기술대학원)
  • Kwon, Ji-Hoon (Radar.EW R&D Center, Hanwha THALES) ;
  • Kang, Seung-Chul (Radar.EW R&D Center, Hanwha THALES) ;
  • Kwak, No-Jun (Graduate School of Convergence Science and Technology, Seoul National University)
  • 투고 : 2016.01.26
  • 심사 : 2016.03.07
  • 발행 : 2016.03.31

초록

본 논문은 추적-후-탐지 처리(TBD: Track Before Detect)를 위한 레이더용 파티클 필터(Particle filter)에 대해서 기술한다. TBD 기법은 강한 클러터 환경, 작은 RCS 타겟 및 스텔스 타겟 등으로 인해 타겟 탐지가 어려운 경우(낮은 SNR)에 적용하는 기술이다. 특히 파티클 필터는 재귀적 TBD(Recursive TBD) 알고리즘 구현에 적합하고, 비선형 모델을 가우시안 선형 모델로 근사화해서 추정하는 칼만 필터 대비, 상대적으로 개선된 정확도를 갖는다. 본 논문에서는 다수의 관측값(클러터 포함)들이 동시에 수신될 때, 신호강도-거리-도플러 정보를 활용하여 파티클 필터 가중치를 직접 계산 및 갱신하는 방식을 제안한다. 성능 분석을 위해 가상의 레이더 시뮬레이션 사니리오를 설정하고, 제안하는 파티클 필터를 적용하여 추적 필터의 추정오차를 분석한다.

This paper describes the technique for Radar Particle filter for TBD(Track Before Detect) processing. TBD technique is applied when target is difficult to detect due to low signal-to-noise ratio caused by strong clutter environments, small RCS targets and stealth targets. Particle filter is suitable for a recursive TBD algorithm and has improved estimation accuracy than Kalman filter. In this paper, we will present a new method of calculating particle weight, when observation values(including strong clutter) are received at the same time. Estimation error performance of the particle filter algorithm is analyzed by using the virtual radar observation scenario.

키워드

참고문헌

  1. D. J. Salmond, H. Birch, "A particle filter for track-before- detect", Proceedings of the American Control Conference, vol. 5, pp. 3755-3760, 2001.
  2. Bocquel, Mélanie, Hans Driessen, and Arun Bagchi, "Multitarget particle filter addressing ambiguous radar data in TBD", Radar Conference(RADAR), pp. 575-580, 2012.
  3. Zhaoping Wu, Tao Su, "Radar target detect using particle filter", Radar Conference 2010 IEEE, pp. 955-958, May 2010.
  4. Y. Boers, J. N. Driessen, "Multitarget particle filter track before detect application", IEE Proceedings-Radar, Sonar and Navigation, pp. 351-357. Dec. 2004.
  5. S. Tugac, M. Efe, "Radar target detection using hidden markov models", Progress in Electromagnetics Research B, vol. 44, 241-259, 2012. https://doi.org/10.2528/PIERB12081603
  6. L. A. Johnston, V. Krishnamurthy, "Performance analysis of a dynamic programming track before detect algorithm", IEEE Transaction on Aerospace and Electronic Systems, vol. 38, pp. 228-242, 2002. https://doi.org/10.1109/7.993242
  7. Shane M. Tonissen, Robin J. Evans, "Performance of dynamic programming techniques for track-before-detect", Aerospace and Electronic Systems, IEEE Transactions on 32.4, pp. 1440-1451, 1996. https://doi.org/10.1109/7.543865
  8. Mark G. Rutten, Neil J. Gordon, and Simon Maskell, "Recursive track-before-detect with target amplitude fluctuations", IEE Proceedings-Radar, Sonar and Navigation, pp. 345-352, 2005.
  9. Mark G. Rutten, Branko Ristic, and Neil J. Gordon, "A comparison of particle filters for recursive track-beforedetect", Information Fusion, 2005 8th International Conference on, vol. 1, pp. 169-175, 2005.
  10. Biruk K. Habtemariam,, Ratnasingham Tharmarasa, and Thia Kirubarajan, "PHD filter based track-before-detect for MIMO radars", Signal Processing, pp. 667-678, 2012.
  11. Y. Boers, J. N. Driessen, "Particle filter based detection for tracking", American Control Conference, vol. 6, pp. 4393-4379, 2001.