一种基于最大选择的Switching-CFAR检测器
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国防科技大学优秀研究生创新基金资助项目(S090401)


A Switching-CFAR Detector Based on Greatest Selection
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对传统CFAR(Constant False Alarm Rate)检测器不能同时适应于均匀和非均匀杂波背景的问题,提出了一种改进的CFAR检测器,即IEGOS(Iterative Excision Greatest of Switching)-CFAR检测器。在迭代删除的基础上,采用Switching方法,利用检测单元幅度自适应选择参考单元,得到前后滑窗的局部杂波功率估计,然后取二者中的最大值作为总的杂波功率估计,实现恒虚警检测。在SwerlingⅡ型目标和瑞利包络杂波分布的假设下,推导证明了IEGOS的恒虚警性,与CA、GO、SO、OS和EXS算法的对比分析表明IEGOS在均匀杂波、多目标干扰和杂波边缘中均拥有较好的性能,且该算法无需排序,便于工程实现。

    Abstract:

    For traditional CFAR detection, the detectors cannot adapt to homogenous and non-homogenous environment simultaneously, so a modified CAFR detector (IEGOS CFAR) is proposed based on greatest selection in this paper. Using the switching method, the local clutter power estimates in leading window and trailing window were obtained by choosing the reference cells adaptively, then the greatest of them was taken as the total clutter power estimate to realize the CFAR detection. Under the assumption of Swerling Ⅱ target and Rayleigh distribution clutter, the CFAR property was proved. Comparisons between CA, GO, SO ,OS and EXS detectors show that IEGOS owns better performance both in homogenous and non-homogenous environment caused by interference and clutter edge. The detector is suitable for application since no sample ordering is needed.

    参考文献
    相似文献
    引证文献
引用本文

郭裕兰,欧建平,张军,等.一种基于最大选择的Switching-CFAR检测器[J].国防科技大学学报,2010,32(5):92-97,117.
GUO Yulan, OU Jianping, ZHANG Jun, et al. A Switching-CFAR Detector Based on Greatest Selection[J]. Journal of National University of Defense Technology,2010,32(5):92-97,117.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2010-04-20
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2012-08-28
  • 出版日期:
文章二维码