OSGO-和OSSO-CFAR在K分布杂波背景下的性能分析

该文证明了形状因子已知条件下OSGO-CFAR和OSSO-CFAR检测器在均匀统计独立的K分布杂波背景下具有恒虚警性能,分析了两种检测器在均匀杂波背景、杂波边缘和存在强干扰目标情况下的检测性能。并与OS-CFAR进行了比较,结果表明OSGO-CFAR在均匀杂波背景和存在强干扰目标情况下带来的附加检测损失很小, 在杂波边缘具有更好的虚警控制能力。所以,OSGO-CFAR是K分布杂波背景下一种性能比较好的恒虚警检测器。     

Log-normal分布杂波背景下有序统计恒虚警检测器性能分析

该文证明了在形状参数已知的均匀对数-正态(Log-normal)杂波背景下有序统计恒虚警(OS-CFAR)检测器能保持恒虚警的特性,导出了该背景下OS-CFAR检测器对非起伏目标的检测性能表达式和平均判决阈值(ADT)表达式。最后用数值方法讨论了最佳序值的选取以及OS-CFAR检测器在取不同参考单元数时相对于理想CFAR的信杂比损失。     

两种具有自动筛选技术的广义有序统计恒虚警检测器及其在多目标…

本文提出两种广义修正的有序统计恒虚警（ＯＳ－ＣＦＡＲ）检测器和一种自动筛选技术。对这两种新的ＯＳ－ＣＦＡＲ检测器，在Ｓｗｅｒｌｉｎｇ ２型目标假设下我们推出了虚警和检测概率及度量平均判决门限的解析表达式。在均匀背景和强干扰目标情况下，文中分析了它们的检测性能，并把它们与几个以前提出的恒虚警处理器进行了比较。     

OSSO和OSGO恒虚警检测器在Pareto分布混响背景下的性能分析

Pareto分布是一种重要的非高斯分布,被证明能够有效描述高分辨率主动声纳的混响统计特性。文章分析了有序统计选小(Ordered Statistic with Smallest Option, OSSO)和有序统计选大(Ordered Statistic with Greatest Option, OSGO)两种恒虚警(Constant Fales Alarm Rate, CFAR)检测器在Pareto分布混响背景下的性能。在尺度参数已知情况下,证明了OSSO-CFAR和OSGO-CFAR对形状参数具有恒虚警的特性。进一步分析了两种检测器在均匀Pareto混响背景、多目标干扰及混响边缘情况下的性能,并与有序统计(Ordered Statistic, OS)CFAR进行了对比。结果表明,在均匀混响背景下,OSGO-CFAR的检测性能与OS-CFAR相近,在混响边缘情况下具有最好的虚警控制能力;而对于多目标干扰情况,OSSO-CFAR比其他两种检测器的检测性能更优。      

非高斯背景下高分辨雷达CFAR检测器

本文讨论了球不变随机过程（ＳＩＲＰ）非高斯杂波背景下高分辨雷达距离扩展目标检测问题。文中提出了ＣＡ—ＣＦＡＲ、ＯＳ—ＣＦＡＲ两种距离扩展目标检测器。文中证明了它们的形状因子和尺度因子未知的情形下具有恒虚警性,即双参数恒虚警性,并分析了这两种检测器的检测性能。这两种检测器亦可用作ＳＩＲＰ杂波背景下低分辨雷达检测器。     

一种低复杂度的OS-CFAR排序算法

有序统计恒虚警算法是雷达在多目标环境下检测目标的主要方法,数值排序是有序统计恒虚警算法的必要步骤,通常采用的排序算法有希尔排序和快速排序等,本文根据OS-CFAR前后检测单元背景窗有相同单元的特点,提出了一种低复杂度的排序算法,仿真结果表明该算法较常规排序算法在运算复杂度上有很大的改善。     

基于杂波分布特性的恒虚警率检测器设计

针对单元平均恒虚警率(CA-CFAR)检测器在非平稳环境下检测性能下降的问题,提出了一种基于杂波分布特性的自适应恒虚警率检测器设计方法。主要思路为：在已知背景杂波类别的前提下,选择相匹配的恒虚警率检测器来提高目标的检测性能。基于实测数据,通过在不同杂波类别的区域人工加运动目标的方式,经过与CA-CFAR检测结果的仿真实验对比,验证了所提恒虚警率检测器的有效性。     

广义Pareto分布海杂波背景下非相干检测器恒虚警性能分析

该文在广义Pareto分布海杂波背景下研究了单元平均(CA)和有序统计量(OS)两种非相干检测器的恒虚警(CFAR)性质,推导了两种非相干检测器的虚警概率公式,发现了两种检测器对杂波的尺度参数是恒虚警的。然而,两种检测器对杂波的散斑协方差矩阵结构和杂波形状参数是非恒虚警的。为了实现全场景的恒虚警检测,预先通过白化方法将具有相关性的海杂波去相关,并通过查表方法使用了匹配杂波形状参数、累积脉冲数和参考单元数的检测门限。在这种情况下,实验结果表明两种非相干检测器能确保全场景恒虚警。     

广义Pareto分布海杂波背景下非相干检测器恒虚警性能分析

该文在广义Pareto分布海杂波背景下研究了单元平均(CA)和有序统计量(OS)两种非相干检测器的恒虚警(CFAR)性质,推导了两种非相干检测器的虚警概率公式,发现了两种检测器对杂波的尺度参数是恒虚警的.然而,两种检测器对杂波的散斑协方差矩阵结构和杂波形状参数是非恒虚警的.为了实现全场景的恒虚警检测,预先通过白化方法将具有相关性的海杂波去相关,并通过查表方法使用了匹配杂波形状参数、累积脉冲数和参考单元数的检测门限.在这种情况下,实验结果表明两种非相干检测器能确保全场景恒虚警.     

基于FPGA的OS-CFAR设计与实现

有序统计恒虚警率处理(OS-CFAR)是现代雷达信号处理的一种重要方法。本文首先简要介绍了OS-CFAR的算法模型,其次通过对数据流的分析,依据OS-CFAR算法的特点,提出一种基于FPGA的实现方案,并详细阐述了用FPGA实现OS-CFAR的两个关键技巧,最后给出了实现结果。     

PERFORMANCE OF TWO GENERALIZED ORDER STATISTICS CFAR DETECTORS WITH AUTOMATIC CENSORING TECHNIQUE IN MULTIPLE TARGET SITUATIONS

This paper presents two generalized modified OS-CFAR detectors and an automatic censoring technique. For these two new OS-CFAR detectors, analytic expressions of the false alarm rate, the detection probabilities and the measure of ADT under the Swerling 2 assumption are obtained. Their detection performances are analyzed in homogeneous background and in the presence of strong interfering targets, and they are compared with several previously proposed CFARs.     

Threshold optimization of decentralized CFAR detection in weibull clutter using genetic algorithms

The use of genetic algorithms (GAs) tool for the solution of distributed constant false alarm rate (CFAR) detection for Weibull clutter statistics is considered. An approximate expression of the probability of detection (P _D) of the ordered statistics CFAR (OS-CFAR) detector in Weibull clutter is derived. Optimal threshold values of distributed maximum likelihood CFAR (ML-CFAR) detectors and distributed OS-CFAR detectors with a known shape parameter of the background statistics are obtained using GA tool. For the distributed ML-CFAR detection, we consider also the case when the shape parameter is unknown of the Weibull distribution. A performance assessment is carried out, and the results are compared and given as a function of the shape parameter and of system parameters.     

Optimum second threshold for the CFAR binary integrator in Pearson-distributed clutter

In this paper, we propose to analyze the binary integration of the cell-averaging constant false-alarm rate (CA-CFAR) and order statistics constant false-alarm rate (OS-CFAR) detectors in the presence of non-Gaussian spiky clutter modeled as a Pearson distribution. We derive new closed form expressions for false alarm and detection probabilities for the CA-CFAR detector in the presence of Pearson-distributed clutter backgrounds. We first show that the use of binary integration improves the detection probabilities of the detectors considered. Secondly, the maximum of detection probability occurs for an optimum choice when the second threshold is set to be equal to M = (3/4) L. For this optimum M-out-of-L rule, the comparison analysis of the CA-CFAR and OS-CFAR binary integrators showed that the latter has better performance in homogeneous Pearson- distributed clutter.     

分布式OS-CPAR检测在多脉冲非相干积累条件下的性能分析

在非均匀杂波背景中和两个局部检测器的条件下,本文分析了分布式OS-CFAR检测在多脉冲非相干积累条件下的性能,与单脉冲检测,单传感器检测以及相应的最优固定阈值检测进行了对比。结果表明,多脉冲积累使分布式检测的性能有明显增强,脉冲积累数的增加使之与最优固定阈值检测的差距减小．而且尽管脉冲积累数的增加使分布式检测相对于单传感器检测的优势减弱,但是优势依然存在,并且在信噪比较低时较为明显。     

一种基于检测单元统计特性的CFAR

针对在多目标、强干扰非均匀环境下CA-CFAR、OS-CFAR检测器的检测性能严重下降的问题,本文提出一种基于检测单元统计特性来选择参考单元的CFAR.分析结果表明,相比于CA-CFAR、OS-CFAR,该CFAR在均匀环境中具有较小的损失,在非均匀环境中,具有较强的抗干扰能力.     

机载雷达多杂波分布类型的恒虚警检测方法

本文提出了一种检验杂波分布类型的有效方法,该方法首先通过概率密度变换方法对被检验的杂波序列进行变换,再应用简单的正态分布检验方法检验变换后的序列,以此来检验原杂波序列的分布类型.针对常用的瑞利、韦布尔、对数正态杂波类型,与χ²和KS拟合检验方法进行了仿真比较,结果表明该方法检验精度高,计算简单,并且通用性强,克服了经典检验方法受区间划分影响大,对参数估计精度要求高,计算复杂的缺点.在杂波检验的基础上,根据OS-CFAR和log-t CFAR检测方法设计了适应于多杂波分布类型的CFAR处理器,对特定杂波类型CFAR检测器与背景杂波类型失配的各种情况的检测性能进行了仿真和分析.     

Heterogeneous performance evaluation of sophisticated versions of CFAR detection schemes

The detection of radar targets in a background, the statistical parameters of which are unknown and may not be stationary, can be effectively achieved through CFAR processors. The CA-CFAR scheme performs optimally for homogeneous and exponentially distributed clutter observations. However, it exhibits severe performance degradation in the presence of outlying target returns in the reference set or in regions of abrupt change in the background clutter power. The OS-CFAR processor has been proposed to solve both of these problems. Although this processor may treat target multiplicity quite well, it lacks effectiveness in preventing excessive false alarms during clutter power transitions. The TM-CFAR algorithm, which implements trimmed averaging after ordering, can be considered as a modified version of OS technique. By knowingly trimming the ordered samples, the TM detector may actually perform better than the OS processor. To simultaneously exploit the merits of CA, OS, and TM schemes, two combinations namely CAOS and CATM have been suggested. Each one of these versions optimizes good features of two CFAR detectors, depending on the characteristics of clutter and searched targets, with the goal of enhancing the detection performance under constant level of false alarm. It is realized by parallel operation of two standard types of CFARschemes. Our goal in this paper is to analyze these two developed versions in heterogeneous situations, to show to what extent they can improve the behavior of the conventional CFAR processors.