Performance Improvement of a Variability-index CFAR Detector for Heterogeneous Environment

비균질 환경에 강인한 검출기를 위한 변동 지수 CFAR의 성능 향상

  • Received : 2011.12.26
  • Accepted : 2012.03.19
  • Published : 2012.03.25

Abstract

In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.

레이더 및 소나와 같은 탐지 시스템에서 잡음 환경은 균질 (homogeneous) 환경과 비균질 (heterogeneous) 환경으로 구분되며 비균질 환경은 간섭 신호 환경 (target masking)과 클러터 경계 환경 (clutter edge)으로 모델링 할 수 있다. VI (variability index) CFAR (constant false alarm rate)는 이러한 다양한 잡음 환경에 강건한 표적신호 탐지 성능의 확보를 위한 방법으로서, mean-level CFAR 알고리즘들 중에서 주어진 잡음 환경에 최적화된 기법을 선택하는 방법이다. 하지만, VI CFAR의 경우 클러터 잡음 경계 환경과 간섭 신호 환경에서 검출 확률이 저하되는 단점을 보인다. 이를 극복하기 위해, 본 논문에서는 TM (trimmed mean) CFAR와 sub-window를 이용하여 비균질 환경에 의한 검출 확률의 저하를 최소화시키는 방법을 제안한다. 모의 전산 실험 결과에 따르면, 제안된 알고리즘은 기존의 VI CFAR 및 단일 CFAR 알고리즘에 비해 간섭 신호 환경과 클러터 경계 환경에서 검출 확률 및 오경보 확률 측면에서 우수한 성능을 보인다.

Keywords

References

  1. Alberto Leon-Garcia, "Probability statistics and random processes for electrical engineering third edition," Pearson, pp.453-466, 2008.
  2. P.P.Gandhi, "Analysis of CFAR processors in nonhomogeneous background," IEEE Trans. on Aerospace and Electronic Systems, Vol.24, No.4, pp.427-445, July1988.
  3. Rohling, H., "Radar CFAR thresholding in clutter and multiple target situations," IEEE Trans. on Aerospace and Electronic Systems, Vol 19, No. 4, pp.608-621, July 1983.
  4. T.-T.V.Cao, "Constant false alarm rate algorithm based on test cell information," IET Radar Sonar Navig, Vol.2, No.3, pp.200-213, June 2008. https://doi.org/10.1049/iet-rsn:20070133
  5. El Mashade, M.B., "Detection performance of the trimmed-mean CFAR processor with noncoherent integration," Radar, Sonar, and Navigation, IEE proceedings, Vol. 142, No.1, pp.18-24, Feb 1995. https://doi.org/10.1049/ip-rsn:19951626
  6. Ritcey, J.A, "Performance analysis of the censored mean-level detector," IEEE Trans. on Aerospace and Electronic Systems, Vol. 22, No. 4, pp.443-454, July 1986.
  7. Finn, H.M, "A CFAR design for a window spanning two clutter fields," IEEE Trans. on Aerospace and Electronic Systems, Vol 22, No. 2, pp.155-169, Mar 1986.
  8. 홍성원, 한동석, "다중 수중 표적 환경에 강인한 OSR CFAR 알고리듬," 전자공학회논문지, 제 48권 TC편, 제4호, 47-52쪽, 2011년 4월
  9. R.Srinivasan, "Robust radar detection using ensemble CFAR processing," Radar, Sonar and Navigation, IEE proceedings, Vol 147, No. 6, pp.291-297, Dec 2000.
  10. M..E.Smith, P.K.Varshney, "Intelligent CFAR processor based on data variability," IEEE Trans. on Aerospace and Electronic Systems, Vol.36, No.3, pp.837-847, July 2000. https://doi.org/10.1109/7.869503
  11. M..E.Smith, "Application of the Variability Index(VI) statistic to radar CFAR processing," Doctor's thesis, Syracuse University, Aug 1997.