利用逆正态得分函数修正秩的非参量检测器

提出了2种新型基于修正秩检验的非参量检测器:广义符号修正秩检测器和Mann-Whitney修正秩检测器.通过Monte-Carlo仿真分析了这2种检测器对起伏雷达目标的检测性能,并分别与4种经典的非参量检测器:广义符号检测器、Mann-Whitney检测器、修正秩方检测器和Savage检测器的检测性能进行了比较.广义符号修正秩和Mann-Whitney修正秩检测器是通过设计秩统计量的逆正态得分函数来获得检验统计量,通过Monte-Carlo仿真实验得出比修正前的非参量检测器有更好的检测性能.这2种新型修正秩检测器对积累分布函数连续且概率密度函数服从对称分布的数据具有恒虚警性能.     

K分布杂波下雷达导引头检测器设计

 针对K分布杂波下雷达导引头平方律检测器检测性能急剧下降这一问题,设计了一种性能较好、易于实现的雷达导引头检测器.首先,结合K分布的复合高斯特性,推导得到了多次观测下的多维K分布联合概率密度函数;然后,采用广义似然比检验,推导得到了广义似然比检验统计量;鉴于该统计量实现困难,通过对导引头接收信号进行预处理,实现了杂波预白化和目标信号能量累加,同时大大简化了广义似然比检验统计量,基于简化的统计量,给出了检测器结构.最后,以导引头检测Swerling I型目标为例,理论分析与仿真实验相结合,分析了所设计检测器的检测性能,仿真结果验证了检测器的有效性.     

海杂波中非参量恒虚警检测器性能分析

主要研究四种非参量恒虚警检测器在实测海杂波数据中对起伏目标的检测性能,给出了不同检测器的检测性能曲线并得到了有意义的结论。目前绝大多数雷达系统的恒虚警处理都是采用参量的方法,而非参量的方法由于其运算的复杂性导致其很难应用于实际的雷达系统。随着高速计算机在现代雷达系统中的应用,使得用非参量的方法实现雷达目标检测成为可能。文中采用X波段雷达实测海杂波数据作为背景杂波,雷达目标采用Swerling起伏目标模型。     

秩和非参数检测器在杂波边缘中的性能

人们常用Rohling教授提出的3种典型背景即均匀背景、多目标和杂波边缘来对检测器的恒虚警率(CFAR)性能进行衡量,但在现有的文献中缺乏秩和(RS)非参数检测器在杂波边缘中虚警概率的解析表达式,缺乏RS检测器与经典的参量型恒虚警率(CFAR)检测器在杂波边缘中虚警控制能力的比较,这在理论研究上是不完整、不全面的。该文给出了RS检测器在杂波边缘中虚警概率的解析表达式,并比较了它与非相干积累单元平均(CA),选大(GO)和有序统计(OS)恒虚警方法在杂波边缘中的虚警控制能力。可以看出,在强、弱杂波均为瑞利分布的情况下,RS检测器在杂波边缘的虚警控制能力处于非相干积累CA方法和非相干积累OS方法之间。但是当长拖尾分布的非高斯杂波进入参考滑窗时,非相干积累CA, GO和OS参量型检测方法的虚警概率都产生了3个以上数量级的上升,且不能回到原始设定的虚警概率。而RS检测器显示出了非参量检测器的优势,即当杂波背景的分布类型发生变化后,它仍然可以保持虚警概率的恒定。     

韦布尔杂波下非参数量化秩检测器的性能

 非参数量化秩(RQ)恒虚警率检测器在雷达目标检测中占据着重要的地位,本文采用解析的方法分析了量化秩检测器在韦布尔分布中的检测性能,并考虑了均匀杂波背景和多目标环境情形,目标模型为Swerling II型.本文给出了非参数量化秩检测器在韦布尔杂波背景中的虚警概率和检测概率的解析计算表达式,并与参量型单元平均(CA)检测器的检测性能进行了对比.     

K分布雷达杂波中两种非参量检测器性能分析

分析了广义符号检测器(GSD)和秩二元累积检测器(RQD)两种非参量检测器在独立和相关K分布杂波下的检测性能.Monte Carlo数值试验表明,GSD在独立K分布杂波拖尾特性越明显时,达到指定检测概率所需要的信杂比越小,而RQD则与之相反.针对独立K分布杂波,RQD的第一检测门限等于参考单元数时可获得较好的检测性能.当参考单元数大于24时,继续增加参考单元数目对于提高两类检测器的检测性能的效果不明显.同时,两类检测器在相关K分布杂波下的虚警概率均会急剧增加,难以完成相关K分布下的CFAR检测.     

雷达非参量检测器在Weibull杂波中的性能

本文采用计算机Monte Carlo模拟方法研究雷达广义符号检验法(GS)检测器及其两种简化形式在Weibull杂波中的性能。给出了模拟计算的定量结果,详细讨论了Weibull杂波形状参数、目标起伏特性和检测器参数对雷达性能的影响。     

无参考数据的分布目标知识辅助检测

该文利用待检测单元杂波协方差矩阵的先验信息，基于贝叶斯方法，研究无参考数据条件下的分布目标的知识辅助检测问题。首先针对非均匀场景，假定各个距离单元杂波协方差矩阵依概率1不相等，给出了广义似然比检验和最大后验-广义似然比检验两种检测器。然后针对均匀杂波场景，给出了单步和双步广义似然比检验两种检测器。进一步利用计算机仿真分析了先验模型失配条件下的检测器性能。分析结果表明，先验模型参数u较小时，检测器性能与先验模型匹配程度密切相关。当u趋于无穷大时，该文给出的几种检测算法性能趋于相同。     

复合高斯杂波中距离扩展目标的参数化Wald检测

本文研究复合高斯杂波环境中的距离扩展目标的自适应检测问题。有色杂波采用参数未知的自回归（AR）过程描述。结合Wald检测准则,仅需对H1假设条件下的未知参数进行最大似然估计,给出了一种新的基于参数化模型的扩展目标检测器——参数化Wald检测器。该检测器的检验统计量可解释为首先针对各个待测单元分别计算检验统计量,然后将所有待测单元的输出进行非相参累加,其对杂波的随机功率起伏具有恒虚警率(CFAR)特性。相比于常规的基于协方差矩阵的检测方法,参数化检测算法的执行过程不需要依赖辅助数据,仅利用待测扩展目标数据即可实现自适应处理,有效缓解了训练压力并降低了计算量。仿真实验表明,所提出的参数化Wald检测器的检测性能优于之前提出的参数化广义似然比检测器的性能。      

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。     

The Performance Characteristics of Two Extensions of the Sign Detector

Two related techniques have been proposed in the past for improving the performance of the sign detector through higherorder data quantization. The fixed-thresholdm-interval detector and the generalized sign detector using a conditional test are both nonparametric detectors which are fairly simple to implement. In this paper we compare the asymptotic and finite-sample, finite-signal performance characteristics of these two detectors, and point out their relative advantages and disadvantages.     

Generalizations of the Sign Detector Based on Conditional Tests

Generalizations of the simple sign detector are considered for nonparametric detection. Nonparametric operation is obtained with only a symmetry assumption on the noise density functions, by basing the detectors on conditional statistical tests. The performance (both asymptotic and finite-sample, finite-signal) of the generalized sign detector is shown to be very good compared to the Wilcoxon detector and to the linear detector, whereas the detector structure remains simple.     

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。      

Locally optimum detection of signals in a generalized observationmodel: the random signal case

Locally optimum detectors for weak random signals are derived for a generalized observation model incorporating signal-dependent and multiplicative noise. It is shown that the locally optimum random-signal detectors in the generalized observation model are interesting generalizations of those that would be obtained in the purely additive noisy signal model. Examples of explicit results for the locally optimum detector test statistics are given for some typical cases. Both asymptotic and finite sample-size performances of the locally optimum detectors are considered and compared with those of other standard detector structures     

PN code acquisition using signed-rank-based nonparametric detectorsin DS/SS systems

In this paper, signed-rank based nonparametric detectors are used for pseudonoise (PN) code acquisition in direct-sequence spread-spectrum (DS/SS) systems. We first derive the locally optimum rank (LOR) detector and then propose the locally suboptimum rank (LSR) and modified signed-rank (MSR) detectors using approximate score functions. We compare the single-dwell scheme without the verification mode using the proposed LSR and MSR detectors with that using the conventional squared-sum (SS) and modified sign (MS) detectors. From the simulation results, it is shown that the proposed LSR and MSR detectors perform better than the MS detector by about 2-3 dB and are nearly optimum     

基于删除平均和单元平均的CFAR检测器性能分析

基于删除平均(CM)和单元平均(CA),提出了一类恒虚警率(CFAR)检测器,其采用CM和CA产生局部估计,再对局部估计进行平均、选大、选小等逻辑运算实现对杂波功率的估计。分析了所提3种检测器的在均匀和非均匀背景下的检测性能。结果表明,在均匀背景和多目标环境下,对局部估计进行平均的检测器性能最优。     

Noise Enhanced Nonparametric Detection

This paper investigates potential improvement of nonparametric detection performance via addition of noise and evaluates the performance of noise modified nonparametric detectors. Detection performance comparisons are made between the original detectors and noise modified detectors. Conditions for improvability as well as the optimum additive noise distributions of the widely used sign detector, the Wilcoxon detector, and the dead-zone limiter detector are derived. Finally, a simple and fast learning algorithm to find the optimal noise distribution solely based on received data is presented. A near-optimal solution can be found quickly based on a relatively small dataset.      

Linear multiuser detectors for synchronous code-divisionmultiple-access channels

Under the assumptions of symbol-synchronous transmissions and white Gaussian noise, the authors analyze the detection mechanism at the receiver, comparing different detectors by their bit error rates in the low-background-noise region and by their worst-case behavior in a near-far environment where the received energies of the users are not necessarily similar. Optimum multiuser detection achieves important performance gains over conventional single-user detection at the expense of computational complexity that grows exponentially with the number of users. It is shown that in the synchronous case the performance achieved by linear multiuser detectors is similar to that of optimum multiuser detection. Attention is focused on detectors whose linear memoryless transformation is a generalized inverse of the matrix of signature waveform crosscorrelations, and on the optimum linear detector. It is shown that the generalized inverse detectors exhibit the same degree of near-far resistance as the optimum multiuser detectors. The optimum linear detector is obtained     

On sequential sign detection of a constant signal

In fixed sample size signal detection, the sign detector is easier to implement and requires much less knowledge of the noise density than does the optimum fixed sample size detector. These advantages accrue at a cost of more observations needed to achieve the same performance. By utilizing the sign detector sequentially, it is shown that considerable saving in the (average) number of observations is obtained over the corresponding optimal fixed sample size detector. The asymptotic relative efficiencies, as the signal-to-noise ratio and both probabilities of error approach zero, of the sequential sign detector compared to fixed sample size detectors are derived. The possibility of truncating the test to avoid excessively large numbers of observations is considered.