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杂波边缘     
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  clutter edge
     Performance analysis of OSGO-CFAR detector in K-distribution clutter edge
     OSGO-CFAR在K分布杂波边缘中的性能分析
短句来源
     Their detection performance in clutter edge region are analyzed and simulated by the MonteCarlo method.
     在精确跟踪杂波的条件下,该检测方法在杂波边缘区与传统的CA、GO-CFAR方法比较具有良好的抗杂波边缘特性,接近理想检测性能。
短句来源
     The performance of the Ordered Statistic with Greatest Option CFAR(OSGO-CFAR) detector in K-distribution clutter edge is studied.
     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。
短句来源
     This paper first studies our nation's certain type of Radar's MGO-CFAR detector , mainly analyzing the detector's performance under homogeneous background, multiple targets situation and clutter edge situation.
     本论文首先对我国某型号雷达中的MGO-CFAR检测器进行分析论证,重点分析了MGO-CFAR检测器在均匀背景杂波、多目标环境和杂波边缘环境中的性能。
短句来源
     The analytic expressions of false alarm probabilities in K-distribution clutter edge and its performance against the clutter edge is analyzed. The OSGO-CFAR detector is compared with the OS,CA and OSSO detectors. The results show that among these detectors the OSGO-CFAR detector has the best performance against the K-distribution clutter edge.
     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。
短句来源
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  clutter edges
     Compared to OS-CFAR, OSGO-CFAR has little additional detectability loss against uniform clutter background and multiple target environments, and it has improved control ability of false alarm against clutter edges.
     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。
短句来源
     It is shown that the detection performance of TMGO is superior to that of GOSGO or OSGO in both homogeneous background and nonhomogeneous environment caused by strong interfering targets and clutter edges, while the sample sorting time of TMGO is less than a half of that of OS.
     分析结果表明,它在均匀背景及多目标和杂波边缘引起的非均匀背景中的性能,均比GOSGO或OSGO获得了改善,并且它的样本排序时间还不到OS的一半。
短句来源
     This paper proves that Ordered Statistic with Greatest Option CFAR(OSGO-CFAR) and Ordered Statistic with Smallest Option CFAR(OSSO-CFAR) are also of CFAR under homeomorphic independent K-distributed clutter background when the shape parameter is known. The performance of two detectors is analyzed against uniform clutter background, clutter edges and multiple target environments.
     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。
短句来源
     Under the assumption of Swerling II target and Rayleigh distributed clutter model, the analytic expressions of Pfa ,Pd, ADT and the peak of false alarm rate at clutter edges are derived.
     在SwerlingⅡ型目标及瑞利杂波假设下,推导出了它的P_(fa)、P_d、ADT及杂波边缘虚警尖锋的数学解析表达式。
短句来源
     The analytic results show that an improved performance over TM is obtained both in homogeneous background and in clutter edges situation,and QBW exhibits robustness in multiple interfering targets environment.
     分析结果表明,它在均匀背景和杂波边缘背景中的性能均比TM获得了改善,同时对多目标也呈现了较好的鲁棒性。
短句来源
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  “杂波边缘”译为未确定词的双语例句
     Regarding the result of clutter tracking as the background information we propose clutter feature (CF) -CFAR detector and structuring element (SE)-CFAR detector. They are based on different results of clutter tracking.
     我们将杂波跟踪结果作为CFAR处理的背景信息,使杂波边缘估计与CFAR检测分离,提出了基于FCM算法和局部熵算法杂波跟踪的两种CFAR检测方法:杂波属性(clutter feature),CF-CFAR检测器,和杂波结构元素(structuring element),SE-CFAR检测器。
短句来源
     the various performance of the MOSOS-CFAR detector was analyzed. The result shows that the MOSOS-CFAR detector has good performance under the homogenous background, almost the same as that of the MGO-CFAR detector;
     计算分析了MOSOS-CFAR检测器的各种性能,分析表明,MOSOS-CFAR检测器在均匀背景杂波中的检测性能良好,和MGO-CFAR检测器的检测性能相近; 抗杂波边缘能力良好,但是略差于MGO-CFAR检测器;
短句来源
     The detection ability of the MGO-CFAR detector is only a little bit worse than that of the CA-CFAR detector.
     在杂波边缘环境中控制虚警能力优秀,远好于CA-CFAR检测器。
短句来源
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  clutter edge
Again, the isolated target at range bin 150 is detected and the target at range bin 230 is masked by the clutter edge.
      
Figure 19 shows the loss in IF around the clutter edge scenarios of Figure 18, and show that the losses can be substantial.
      
Think about a weak edge at object boundary, or a strong clutter edge in the background.
      
  clutter edges
However, the false alarm rate performance of OSSO-CFAR(Constant False Alarm Rate) scheme at clutter edges is worsen with increasing the postdetection integrated pulses.
      
Notice that after learning, not only clutter edges are suppressed but also the correct edge polarities are recovered.
      
Output from a directional Gaussian edge detector shows that there are many clutter edges present as potential distractors.
      
We want to inhibit clutter edges and recover correct polarity.
      


How to maintain the false-alarm-rate constant of radar detectingsystem is one of the important problems in modern radar technology andsignal processing technology.In order to obtain constant-false-alarm-ratein the complex clutter surrounding,radar detecting system must have aconstant-false-alarm-rate processor(CFAR Processor).The AC-CFARprocessor discussed in this paper is a new processor.Its CFAR thresholdis implemented by selecting a mean value which approaches the detecteddistance-cell value.On the basis...

How to maintain the false-alarm-rate constant of radar detectingsystem is one of the important problems in modern radar technology andsignal processing technology.In order to obtain constant-false-alarm-ratein the complex clutter surrounding,radar detecting system must have aconstant-false-alarm-rate processor(CFAR Processor).The AC-CFARprocessor discussed in this paper is a new processor.Its CFAR thresholdis implemented by selecting a mean value which approaches the detecteddistance-cell value.On the basis of simple hardware-implement,the AC-CFAR processor has an adaptive performance which can timely reflect thechanges of external clutter,and a very good perfermance of anti-multitargeteffect and anticlutter edge effect as well.It can also resist the effect ofb“igtarget eat small target”and reduce CFAR loss.

如何维持雷达检测系统恒定的虚警率是现代雷达技术和信号处理技术中重要的问题之一。为使雷达检测系统在复杂的杂波环境中获得恒定的虚警率,就需要有高性能的恒虚警(CFAR)处理器。本文提出的新型CFAR 处理器选择一个与被检测距离单元的值相接近的均值来作为CFAR 的门限,从而使这种处理器具有能够及时反映外部杂波环境变化的自适应性;它硬件实现简单,具有很好的抗多目标效应、抗杂波边缘效应、抗大目标“吃”小目标效应以及降低(CFAR)损失的性能。

A new CFAR detector(MOSTM )based on order statistics(OS )and trimmed mean (TM)is proposed in this paper.It takes the mean value of OS and TM local estimations as a noise power estimation ,and it also uses the automatic censoring technique proposed by[4]. Under Swerling Ⅱ assumption ,the analytic expressions of P_(fa).P_d and ADT are derived for the detector. By comparison with other schemes ,the results show that the detection performance of MOSTM is improved both in homogenius background and in nonhomogenious...

A new CFAR detector(MOSTM )based on order statistics(OS )and trimmed mean (TM)is proposed in this paper.It takes the mean value of OS and TM local estimations as a noise power estimation ,and it also uses the automatic censoring technique proposed by[4]. Under Swerling Ⅱ assumption ,the analytic expressions of P_(fa).P_d and ADT are derived for the detector. By comparison with other schemes ,the results show that the detection performance of MOSTM is improved both in homogenius background and in nonhomogenious environment caused by strong interfeting targets and clutter edges ,while the sample sorting time of MOSTM is less than half of hat of OS.

基于有序统计(OS)和剔除平均(TM)提出了一种新的恒虚警检测器(MOSTM),它采用OS和TM来产生局部估计,再对二者平均来实现对杂波功率水平的估计,并应用了文献[4]提出的自动筛选技术。在SwerlingII型目标假设下,推导出了它的P_(fa)、P_d和度量ADT的解析表达式,并与其它方案进行了比较,分析结果表明,MOSTM在均匀背影及多目标和杂波边缘引起的非均匀背景中,它的性能比OS和GOSCA获得了改善,并且它的样本排序时间还不到OS的一半。

In order to make the detector perform robustly, an intuitive solution can be obtained by censoring the clutter observations from large and small deviations. In recent studies, censoring techniques have beenimplemented using order statistics (OS) and trimmed mean (TM) methods. In order to ultilize censored data, wepresent a quasi-best weighted (QBW) order statistics method resulting in an improved detection performancewhile censoring outliers. Based on quasi-best weighted method, a new greatest selection detector...

In order to make the detector perform robustly, an intuitive solution can be obtained by censoring the clutter observations from large and small deviations. In recent studies, censoring techniques have beenimplemented using order statistics (OS) and trimmed mean (TM) methods. In order to ultilize censored data, wepresent a quasi-best weighted (QBW) order statistics method resulting in an improved detection performancewhile censoring outliers. Based on quasi-best weighted method, a new greatest selection detector (QBWGO-CFAR) is proposed in this paper. Both Of its leading and lagging windows use QBW method to create twO localnoise power estimations , the greatest is selected as a globle estimation to set an adaptive threshold. Under the assumption of Swerling Ⅱ target and Rayleigh distributed clutter, the analytic expressions of Pfa, Pd,ADT and thepeak of false alarm at clutter edges are derived. The analytic results show that an improved performance overGOSGO or OSGO is obtained both in homogeneous background and in nonhomogeneous environment caused bystrong interfering targets and clutter edges. In specific cases. QBWGO-CFAR reduces tO GO and MX-CMLD.

为了提高恒虚警检测器在均匀背景中的检测性能及增强对干扰的鲁棒性,本文提出了一种准最佳加权(QBW)有序统计方法.基于这种方法,还提出了准最佳加权最大选择恒虚警检测器(QBWGO-CFAR),它的前、后沿滑窗均采用QBW方法来产生局部估计,将局部估计中的最大值作为检测器对杂波功率水平的估计,设置自适应检测门限,应用文献[3]提出的自动筛选技术在SwerlingⅡ型目标及瑞利杂波假设下,推导出了它的Pfa、Pd、ADT及杂波边缘虚警尖峰的数学解析表达式分析结果表明,它在均匀背景及多目标和杂波边缘引起的非均匀背景中的性能,均比GOSGO或OSGO获得了改善.在特殊情况下,QBWGO退化为GO和MX-CMLD

 
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