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OSCAGO—CFAR检测器在干扰边缘中的性能分析 总被引:2,自引:0,他引:2
本文研究OSCAGO-CFAR检测器在干扰边缘中的性能,文中推导出了它在干扰边缘环境中虚警概率的解析表达式,分析了它抗边缘干扰的性能,并且与GO、OS和CA-CFAR检测器进行了比较。结果表明,OSCAGO的抗边缘干扰性能比这三种CFAR检测器均有明显增强,同时,它在均匀背景和多目标环境中也保持了良好的检测性能。 相似文献
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OSCAGO-CFAR检测器在干扰边缘中的性能分析 总被引:1,自引:0,他引:1
本文研究OSCAGO-CFAR检测器[1,2]在干扰边缘中的性能。文中推导出了它在干扰边缘环境中虚警概率的解析表达式,分析了它抗边缘干扰的性能,并且与GO、OS和CA-CFAR检测器进行了比较。结果表明,OSCAGO的抗边缘干扰性能比这三种CFAR检测器均有明显增强。同时,它在均匀背景和多目标环境中也保持了良好的检测性能。 相似文献
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一种基于排序和平均的新恒虚警检测器 总被引:6,自引:0,他引:6
基于有序统计和单元平均方法及文献中的自动筛选技术,提出了一种新的恒虚警检测器,它被称作排序与平衡均值(MOSCA)处理器。对这种新的恒虚检测器,在SwerlingⅡ型目标假设下,我们获得了虚警和检测概率及度量ADT的解析表达式。在均匀背景和存在强干扰目标的情况下,分析了它的检测性能,并将其与CA和OS-CFAR进行了比较。结果表明MOSCACFAR在均匀干扰背景中的性能位于CA和OS之间,在多目标 相似文献
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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。 相似文献
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本文通过分析现有的五种CFAR处理器检测性能的优劣。提出准有序CFRA方案,并在计算机模拟统计的基础上阐述了该处理器的检测性能,得出POS-CFAR能以较小的检测损失,换取对染波边界、多目标环境有较好适应性的结论。 相似文献
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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… 总被引:3,自引:2,他引:1
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。 相似文献
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宽屏幕电视接收机利用幅形比检测(ASPECTDETECTION)和非线性控制(NON-LINEAR CON-TROL)技术对输入的图像和字幕进行全自动控制,应用推断(FUZZY-INFERENCE)技术进行画质控制。 相似文献
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提出一种新的基于有序统计的恒虚警检测器和一种新的自动筛选技术。这种新的检测器是广义有序统计单元平均(GOSCA)恒虚警算法。对这种新的恒虚警算法在斯威林2型目标假设下,我们获得了虚警概率、探测概率和度量ADT的解析表达式。在均匀背景和强干扰存在的情况下,分析了它的探测性能,并把它与OS-CFAR进行了比较。分析结果表明,GOSCA-CFAR在均匀干扰背景和多目标情况下均具有较好的探测性能,而GOS 相似文献
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多用户检测中盲自适应算法的研究 总被引:2,自引:0,他引:2
多用户检测中的盲目适应算法包括上输出能量(MOE)算法、Sato算法、恒模算法(CMA)和约束恒模算法(C-CMA)。本文比较了以上算法和均方误差(MSE)算法的收敛性能,仿真表明在保证收敛的条件下,CMA或C-CMA算法具有收敛速度快、稳态性能好的优点,因此实际系统中可以先脾MOE算法,当达到稳态后,转到CMA或C-CMA算法上以提高稳态性能,且计算复杂度只有O(N)。 相似文献
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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. 相似文献
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为提高基于二元局部判决的分布式检测系统的检测性能,研究了基于模糊隶属度函数的分布式检测系统融合算法,提出了模糊有序统计融合准则。通过对肼传感器进行分布式检测系统仿真,结果表明:模糊有序统计融合准则在均匀环境中能获得比基于二元判决准则更好的检测性能,也好于同样采用模糊隶属度函数的求和准则的检测性能,且在多目标环境下获得了较强的适应性。 相似文献
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Cui Ningzhou Xie Weixin Yu Xiongnan 《电子科学学刊(英文版)》1997,14(1):7-11
The multisensor detection area partitioning is considered. An approach is presented to the fusion in each detection area where the sensor uses different thresholds and then at system level. The expressions of the detection probability and false alarm probability are given. An application of the method is illustrated to distributed CFAR detection systems. The result shows that the system detection probability may be improved by setting different thresholds for a detector. 相似文献
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Mohamed B. El Mashade 《Radioelectronics and Communications Systems》2013,56(8):385-401
A constant false alarm rate (CFAR) in the presence of variable levels of noise is usually a requirement placed on any modern radar. The CA- and OS-CFAR detectors are the most widely used ones in the CFAR world. The cell-averaging (CA) is the optimum CFAR detector in terms of detection probability in homogeneous background when the reference cells have identical, independent and exponentially distributed signals. The ordered-statistic (OS) is an alternative to the CA processor, which trades a small loss in detection performance, relative to the CA scheme, in ideal conditions for much less performance degradation in nonideal background environments. To benefice the merits of these well-known schemes, two modified versions (MX- and MN-CFAR) have been recently suggested. This paper is devoted to the detection performance evaluation of these modified versions as well as a novel one (ML-CFAR). Exact formulas for their false alarm and detection performances are derived, in the absence as well as in the presence of spurious targets. The results of these performances obtained for Rayleigh clutter and Rayleigh target indicate that the MN-CFAR scheme performs nearly as good as OS detector in the presence of outlying targets and all the developed versions perform much better than that processor when the background environment is homogeneous. When compared to CA-CFAR, the modified schemes perform better in ideal conditions, and behave much better in the presence of interfering targets. 相似文献
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This paper deals with the constant false alarm rate (CFAR) radar detection of targets embedded in Pearson distributed clutter.
We develop new CFAR detection algorithms-notably cell averaging (CA), greatest of selection (GO) and smallest of selection
SO-CFAR operating in Pearson measurements based on a non-linear compression method for spiky clutter reduction. The technique
is similar to that used in non uniform quantization where a different law is used. It consists of compressing the output square
law detector noisy signal with respect to a non-linear law in order to reduce the effect of impulsive noise level. Thus, it
can be used as a pre-processing step to improve the performance of automatic target detection especially in lower generalised
signal-to-noise ratio (GSNR). The performance characteristics of the proposed CFAR detectors are presented for different values
of the compression parameter. We demonstrate, via simulation results, that the pre-processed compression procedure is computationally
efficient and can significantly enhance detection performance. 相似文献