相参雷达K分布海杂波背景下非相干积累恒虚警检测方法

张坤; 水鹏朗; 王光辉

doi:10.11999/JEIT190441

相参雷达K分布海杂波背景下非相干积累恒虚警检测方法

doi: 10.11999/JEIT190441

西安电子科技大学雷达信号处理国家重点实验室西安 710171

基金项目: 国家自然科学基金(61671357)

详细信息

作者简介:
张坤：男，1989年生，博士生，主要研究方向为压缩感知、雷达信号处理和海面目标检测及其参数估计

水鹏朗：男，1967年生，教授，博士生导师，研究方向为雷达目标探测、图像处理和滤波器组设计与应用

王光辉：男，1990年生，硕士生，主要研究方向为海杂波模型建模和目标检测算法

通讯作者:
张坤　xidiankun@163.com；kzhang_1608@stu.xidian.edu.cn

中图分类号: TN959.72
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- 被引次数: 0
出版历程
- 收稿日期: 2019-06-18
- 修回日期: 2020-05-25
- 网络出版日期: 2020-06-04
- 刊出日期: 2020-07-23

Non-coherent Integration Constant False Alarm Rate Detectors against K-distributed Sea Clutter for Coherent Radar Systems

National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Nature Science Foundation of China (61671357)

摘要

摘要:
相参雷达系统下的非相干积累检测方法，可以提高雷达的目标检测速度，达到实时处理的要求。然而，相参雷达系统下的非相干积累检测方法对参考单元数、脉冲积累数、杂波散斑协方差矩阵以及海杂波模型的形状参数均是非恒虚警(CFAR)的。该文基于块白化的海杂波预白化方法，提出预白化单元平均恒虚警(PWCA-CFAR)检测方法和预白化单元中值恒虚警(PWCM-CFAR)检测方法，并使用了匹配于参考单元数、脉冲积累数、形状参数的自适应门限，确保提出检测方法的恒虚警特性。实验结果表明，当存在异常单元时，PWCM-CFAR检测方法的检测性能优于PWCA-CFAR检测方法。
- 相参雷达系统 /
- 非相干积累检测方法 /
- 恒虚警 /
- 海杂波 /
- 块白化
Abstract:
The non-coherent integration detectors for coherent radar systems can promote the detection rate of the radar and meet the required real-time processing, however, these detectors are not Constant False Alarm Rate (CFAR) with respect to the reference cell number, the accumulated pulse number, the clutter speckle covariance matrix, and the shape parameter of the sea clutter model. Based on block-whitening method to whiten the sea clutter, a Pre-Whitening Cell-Averaging CFAR (PWCA-CFAR) detector and a Pre-Whitening Cell-Median CFAR (PWCM-CFAR) detector are proposed where the detection thresholds matching the reference cell number, accumulated pulse number and shape parameter are used. The experiment results show that the PWCM-CFAR detector attains better detection performance than the PWCA-CFAR detector when there exist abnormal cells.
- Coherent radar system /
- Non-coherent integration detectors /
- Constant False Alarm Rate (CFAR) /
- Sea clutter /
- Block-whitening

HTML全文

图 1 CA-CFAR和CM-CFAR的检测统计量在不同脉冲间相关系数下的经验累积分布函数

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图 2 PWCA-CFAR和PWCM-CFAR检测方法的原理框图

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图 3 不同异常分辨单元比例情况下PWCA-CFAR和PWCM-CFAR检测方法的ROC曲线

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图 4 不同形状参数情况下PWCA-CFAR和PWCM-CFAR检测方法的ROC曲线

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图 5 在不同块白化长度下PWCA-CFAR和PWCM-CFAR检测方法的计算时间

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图 6 3组数据的幅度图

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图 7 3组数据的幅度分布拟合结果

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图 8 PWCA-CFAR和PWCM-CFAR检测方法在3组数据不同目标信杂比情况下的检测概率

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