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A new distributed constant false alarm rate detector

机译:新型分布式恒定误报率检测器

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A new constant false alarm rate (CFAR) test termed signal-plus-order statistic CFAR (S+OS) using distributed sensors is developed. The sensor modeling assumes that the returns of the test cells of different sensors are all independent and identically distributed In the S+OS scheme, each sensor transmits its test sample and a designated order statistic of its surrounding observations to the fusion center. At the fusion center, the sum of the samples of the test cells is compared with a constant multiplied by a function of the order statistics. For a two-sensor network, the functions considered are the minimum of the order statistics (mOS) and the maximum of the order statistics (MOS). For detecting a Rayleigh fluctuating target in Gaussian noise, closed-form expressions for the false alarm and detection probabilities are obtained. The numerical results indicate that the performance of the MOS detector is very close to that of a centralized OS-CFAR and it performs considerably better than the OS-CFAR detector with the AND or the OR fusion rule. Extension to an N-sensor network is also considered, and general equations for the false alarm probabilities under homogeneous and nonhomogeneous background noise are presented.
机译:开发了一种新的恒定误报率(CFAR)测试,称为使用分布式传感器的信号加阶统计CFAR(S + OS)。传感器建模假定不同传感器的测试单元的返回值都是独立且均匀分布的。在S + OS方案中,每个传感器将其测试样本及其周围观测值的指定顺序统计信息传输到融合中心。在融合中心,将测试单元样本的总和与常数乘以阶次统计的函数进行比较。对于两传感器网络,考虑的功能是最小顺序统计(mOS)和最大顺序统计(MOS)。为了检测高斯噪声中的瑞利起伏目标,获得了虚警和检测概率的闭式表达式。数值结果表明,MOS检测器的性能与集中式OS-CFAR的性能非常接近,并且其性能远优于具有AND或OR融合规则的OS-CFAR检测器。还考虑了扩展到N传感器网络,并提出了在均质和非均质背景噪声下虚警概率的一般公式。

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