• DocumentCode
    3359443
  • Title

    Distributed adaptive OSWCA CFAR detector

  • Author

    Xiaoyan, Ma ; Jiabin, Xiang ; Jun, Yang

  • Author_Institution
    Dept. of lnf. Eng., Air Force Radar Acad., Hubei, China
  • Volume
    3
  • fYear
    2004
  • fDate
    31 Aug.-4 Sept. 2004
  • Firstpage
    2082
  • Abstract
    In the sense of likelihood ratio test (LRT), a weighted adaptive OSWCA CFAR detector using distributed sensors is proposed in this paper. In the scheme, a local test statistic, which is the ratio of its test sample level and a designated order statistic (OS) of its reference samples, is calculated by each sensor, and then each sensor transmits its local test statistic to the fusion center. At the fusion center, the final decision is made based on weighted cell averaging algorithm (WCA). Since the weights are adjusted according to different signal-to-noise/clutter ratio (SNR), adaptively, the proposed detector can be available in the case of that the target echo and noise/clutter that have different level for each sensor. Unlike many current distributed CFAR detectors, which assuming that all noise/clutter samples satisfy independent identical distributed (IID) and have same SNR for each sensor. Meanwhile, for a Rayleigh fluctuating target in Gaussian noise of unknown level, we obtain its closed-form expressions for the false alarm probability and the detection probability. The numerical analysis results indicate that the proposed OSWCA scheme can be available.
  • Keywords
    Gaussian noise; adaptive radar; adaptive signal detection; distributed sensors; probability; radar clutter; radar detection; radar signal processing; sensor fusion; statistical analysis; Gaussian noise; Rayleigh fluctuating target; detection probability; distributed adaptive OSWCA CFAR detector; distributed sensor; false alarm probability; likelihood ratio test; local test statistic; order statistic; signal-to-noise-clutter ratio; weighted cell averaging algorithm; Adaptive signal detection; Detectors; Gaussian noise; Light rail systems; Noise level; Sensor fusion; Signal to noise ratio; Statistical analysis; Statistical distributions; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
  • Print_ISBN
    0-7803-8406-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2004.1442186
  • Filename
    1442186