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.     

两种恒虚警检测器在干扰边缘中的性能分析

本文研究ＧＯＳＧＯ和ＧＯＳＳＯ－ＣＦＡＲ检测器在干扰边缘中的性能。     

混响背景下基于自动删除算法的恒虚警检测器

该文提出了一种混响背景下基于自动删除算法的恒虚警检测器。该方法可以自动删除参考单元中的干扰点,从而可以克服Barnard等人(2004)提出的方法所存在的缺点。推导了该检测器的平均虚警概率和平均检测概率。最后通过对仿真数据和试验数据的处理结果验证了该检测器的优越性。     

两种恒虚警检测器在干扰边缘中的性能分析

本文研究 GOSGO(Generalised Order Statistics and Greatest Of)和GOSSO(Generalised Order Statistics and Smallest Of)-CFAR检测器在干扰边缘中的性能。文中推导出了它们在干扰边缘环境中虚警概率的解析表达式,分析了它们抗边缘干扰的性能,并且与OS(Order Statistics)、CA(Cell Averaging)、GO(Greatest Of)和SO(Smallest Of)等检测器进行了比较。结果表明,与抗边缘干扰性能较好的GO相比,GOSGO的抗边缘干扰性能又有明显的增强。但是,GOSSO的抗边缘干扰性能却很不理想。     

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。     

K分布杂波背景下次序统计恒虚警检测器的性能

本文证明了在形状因子已知条件下次序统计恒虚警（ＯＳ－ＣＦＡＲ）检测器在Ｋ分布杂波背景下能保持恒虚警的特性，分析了均匀Ｋ分布杂波背景下检测器的性能，研究了不同参考单元数的信杂比损失，对于未知形状因子，本文提出了一种有效的估计方法。     

一种分布式恒虚警检测和融合方法

研究了分布式恒虚警(CFAR)检测在Neyman-Pearson(NP:奈曼-皮尔逊)意义上的最优化问题,阐述了基于二元局部判决与基于局部检测统计量的分布式CFAR检测在最优化上的差别.提出了一类局部检测统计量.证明了基于这种局部统计量的在NP意义上最优的分布式CFAR检测具有似然比检验形式,并且研究了此优化融合方法(OS-S-CA).结果表明,融合可以达到其最优融合接近的性能.     

一类基于VMSR的恒虚警检测器

设计了一类基于VMSR的改进型恒虚警检测器,给出了检测器的检测结构框图,同时描述了该类检测器的检测模型并给出了相应的检测概率表达式。该类检测器通过VR删除算法自适应删除杂波背景中的干扰样本,并将剩余样本按照不同操作得到杂波背景功率估计,提高了复杂杂波背景下检测器的精确性及鲁棒性。通过与典型VMSR-CFAR检测器的仿真对比实验,验证了该类检测器的检测性能。     

方差均值平方比恒虚警检测器

为了提高雷达恒虚警(Constant False Alarm Rate,CFAR)检测器在多目标背景下的鲁棒性,更好地检测目标,提出了一种新的基于方差均值平方比(VMSR)的恒虚警检测器,并建立了相应的检测器模型,得出了标称化因子T值和置信区间(a,b)。在均匀背景和多目标背景下,对VMSR检测器进行了仿真分析。在均匀背景下,VMSR检测性能优于OS,相比CA仅有很小的检测损失;在多目标背景下,VMSR检测性能相比OS得到了提升,特别是在干扰目标个数r>N-k时,OS不能有效检测出目标,而VMSR仍能保持较好的检测性能。结果表明,VMSR在多目标背景下检测性能优于OS,其在多目标背景下具有较强的鲁棒性。     

低通混响滤波器设计及其性能分析

给出了嵌套的低通混响滤波器的统一设计结构。针对一阶FIR,IIR低通滤波器,分析了系统稳定性的条件;同时分析了嵌套结构的低通梳状滤波器性能。仿真结果表明,与其他结构的梳状滤波器相比,嵌套的低通梳状滤波器结构更有效。     

OSGO-CFAR在K分布杂波边缘中的性能分析

研究有序统计选大（OSGO）恒虚警检测器在K分布杂波边缘中的性能。文中推导出了该检测器在K分布杂波边缘中虚警概率的解析表达式，分析了它抗干扰边缘的性能，并与OS、CA、OSSO等检测器进行了比较，结果表明OSGO-CFAR具有最好的抗K分布杂波边缘的性能。     

Numerical and Experimental Analysis of the Performance of a Reduced Surface Stirrer for Reverberation Chambers

通过数值方法和实际测试,分析并验证了减小机械搅拌器叶片面积后搅拌叶的搅拌效率.搅拌效率可通过搅拌器统计独立位置数、工作区域场均匀性和莱斯因子K定量表示.与测量结果比较得知,验证了该数值分析方法的可靠性.     

混响室的仿真与优化

混响室的结构设计中,搅拌器的设计是一个难点.合理设计的搅拌器会改善混响室的场均匀性、降低最低可用频率.文章通过实验仿真,定性分析了不同的搅拌器大小、形状与个数对混响室性能的影响.     

Estimation in a Pareto Distribution: Theory & Computation

This paper treats the theoretical and computational problems of maximum likelihood parameter estimation in a Pareto distribution. Logarithmic likelihood estimating equations and the associated conditional log-likelihood function are derived, and expressions for the asymptotic variances and covariances of the parameters are given. Discussions pertinent to tests of hypotheses and the construction of simultaneous s-confidence contours are provided. The computations required for estimation are illustrated by an example in which the parameters are estimated by numerically maximizing the conditional log-likelihood function and by using an algorithm for global optimization which exploits the mathematical structure of this function. The parameter estimates obtained in this way are guaranteed to be those at which the likelihood function is globally maximum over the space of permissible parameter values. A Fortran program exists for performing these calculations.     

双发射天线对混响室场性能影响的数值分析

提出了双天线激励混响室的方法,研究了双天线激励对混响室场性能的影响。分析了双天线改善混响室场均匀性的原理,对单天线激励下的混响室模型以及处于不同位置的双天线激励下的混响室模型进行了仿真计算,从场均匀性和场强两个方面研究了双天线对混响室场性能的影响,对双天线影响场强的机理进行了分析。研究表明:采用双天线激励改善了混响室工作区域的场均匀性;采用双天线可以降低对功率放大器的要求,降低大型混响室测试成本。最后对双发射天线在大型混响室中的应用进行了探讨和展望。     

镜像对称结构对多馈源混响室场性能的影响

为解决混响室大体积与场性能高要求之间的矛盾,提出了一种基于镜像原理的多馈源混响室的设计思想,从原理上分析了镜像多馈源混响室的可行性和有效性,并通过仿真计算研究了镜像双馈源混响室的场性能.结果表明,在输入功率一定时,两个单混响室系统组合成镜像双馈源混响室后,在工作区域的场均匀性能不下降的基础上,不但可用于电磁兼容测试的工作区域体积大幅度增大,而且测试区域的电场强度也得到了提高.同时,对镜像多馈源混响室进行了进一步的扩展分析,得出了组成镜像多馈源混响室的单混响室系统数量的理论表达式.     

对N次观测Pareto分布参数有效估计范围的扩展

基于 zln(z) 方法的N次观测Pareto分布参数估计不能有效估计形状参数小于1的情形。该文采用 zrln(z) 方法对基于 zln(z) 的方法进行扩展,将N次观测Pareto分布的形状参数的有效估计范围进行扩大。文中推导了N次观测Pareto分布参数估计的表达式,从理论上证明该方法能够估计小于1的形状参数。仿真结果表明：r1 时, zrln(z) 方法能够在该扩大的范围内有效地估计形状参数。     

Performance Analysis of Hybrid Distribution in Human-Centric Multimedia Networking

With the booming of Human-centric mul-timedia networking (HMN), there are rising amount of human-made multimedia that needs to distribute to con-sumers with higher speed and e?ciency. Hybrid distribu-tion of Client/Server (C/S) and Peer-to-Peer (P2P) have been successfully deployed on the Internet and the practi-cal benefits have been widely reported, while its theoretical performance remains unknown for mass data delivery un-fortunately. This paper presents an analytical and experi-mental study on the performance of accelerating large-scale hybrid distribution over the Internet. In particular, this pa-per focuses on the user behavior in HMN and establishes a user behavior model based on the Kermack-McKendrick model in epidemiology. Analytical expressions of average delay in HMN are then derived based on C/S, P2P and hy-brid distribution, respectively. Our simulation shows how to design and deploy a hybrid distribution system of HMN that helps to bridge the gap between system ultilization and quality of service, which provides direct guidance for practical system design.     

Extending the Generalised Pareto Distribution for Novelty Detection in High-Dimensional Spaces

Novelty detection involves the construction of a “model of normality”, and then classifies test data as being either “normal” or “abnormal” with respect to that model. For this reason, it is often termed one-class classification. The approach is suitable for cases in which examples of “normal” behaviour are commonly available, but in which cases of “abnormal” data are comparatively rare. When performing novelty detection, we are typically most interested in the tails of the normal model, because it is in these tails that a decision boundary between “normal” and “abnormal” areas of data space usually lies. Extreme value statistics provides an appropriate theoretical framework for modelling the tails of univariate (or low-dimensional) distributions, using the generalised Pareto distribution (GPD), which can be demonstrated to be the limiting distribution for data occurring within the tails of most practically-encountered probability distributions. This paper provides an extension of the GPD, allowing the modelling of probability distributions of arbitrarily high dimension, such as occurs when using complex, multimodel, multivariate distributions for performing novelty detection in most real-life cases. We demonstrate our extension to the GPD using examples from patient physiological monitoring, in which we have acquired data from hospital patients in large clinical studies of high-acuity wards, and in which we wish to determine “abnormal” patient data, such that early warning of patient physiological deterioration may be provided.