非均匀杂波背景下雷达恒虚警检测技术研究

发布时间：2018-04-27 15:10

  本文选题：非均匀杂波 + 杂波边缘　； 参考：《南京理工大学》2015年硕士论文

【摘要】：雷达信号的恒虚警率(Constant False Alarm Rate, CFAR)处理技术是现代雷达信号处理的重要研究内容之一,在雷达目标自动检测中占有不可或缺的重要地位。CFAR处理技术的理论研究虽然已取得丰硕成果但现有的经典恒虚警检测算法一般难以在不同环境中得到了性能的平衡,而大多恒虚警检测器都面对在非均匀杂波环境下的杂波边缘和多干扰目标环境中检测性能下降的问题。本文在分析了几种典型杂波模型的基础上,针对非均匀杂波背景下的雷达恒虚警检测技术进行了研究。论文的主要工作如下：1)在讨论了瑞利分布、对数正态分布及韦布尔分布等经典杂波分布模型的基础上,以韦布尔分布杂波为例,采用零记忆非线性变换(ZMNL)方法进行了非相干及相关杂波模拟仿真,为后续研究工作奠定基础。2)分析了传统的均值(ML, Mean Level)类和有序统计量(OS, Order Statistics)类的CFAR检测器,仿真比较了其在均匀杂波背景、多干扰目标杂波背景及存在杂波边缘背景下的性能,为后续CFAR检测器的设计讨论提供了性能评估依据。3)针对存在杂波边缘的非均匀杂波背景下,仿真分析了MLC-CFAR、Ⅵ-CFAR等CFAR检测算法,针对Ⅵ-CFAR在杂波边缘漏警概率增大和在多干扰目标环境检测性能下降的缺点,提出了一种多策略CFAR检测器(ACSVI-CFAR)。仿真分析表明ACSVI-CFAR检测器既改善了Ⅵ-CFAR在均匀背景的恒虚警损失及杂波边缘环境下的虚警概率控制能力,同时具有S-CFAR检测器在多干扰目标背景下的优异性能4)针对未知数目的多干扰目标杂波背景环境,在研究了排序数据方差(ODV)删除算法的基础上,仿真分析了基于排序数据方差的自适应删除最大似然恒虚警(ACMLH-CFAR)检测器,针对ACMLH-CFAR检测器在杂波边缘背景检测性能的不足,采用Ⅵ-CFAR算法的均值比对其进行改进,仿真结果表明,改进后的ACMLH-CFAR在杂波边缘性能得到了改善。
[Abstract]:Constant False Alarm rate (CFAR) processing technology of radar signal is one of the important research contents of modern radar signal processing. Although the theoretical research of CFAR processing technology has made a lot of achievements, the existing classical CFAR detection algorithms are generally difficult to achieve a performance balance in different environments. Most CFAR detectors face the problem of poor detection performance in heterogeneous clutter environment and multi-jamming target environment. In this paper, based on the analysis of several typical clutter models, the CFAR detection technology in heterogeneous clutter background is studied. The main work of this paper is as follows: (1) on the basis of discussing the classical clutter distribution models such as Rayleigh distribution, logarithmic normal distribution and Weibull distribution, we take Weibull distribution as an example. The non-coherent and correlated clutter simulation is carried out by using the zero-memory nonlinear transform (ZMNL) method, which lays a foundation for further research. (2) the traditional CFAR detectors of MLL, Mean level class and ordered statistics class are analyzed. Its performance in homogeneous clutter background, multi-jamming target clutter background and clutter edge background is compared by simulation, which provides a basis for performance evaluation for the design and discussion of CFAR detector. 3) for heterogeneous clutter background with clutter edge. The CFAR detection algorithms such as MLC-CFAR and 鈪，

本文编号：1811224