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On distributed detection with correlated sensors: two examples

机译:关于具有相关传感器的分布式检测:两个示例

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The authors study the effect of correlated noise on the performance of a distributed detection system. They consider a suboptimal scheme by assuming that the local sensors have the same operating point, and that the distribution of the sensor observation is symmetric. This implies that the joint distribution of the sensor decisions, and therefore the fusion rule, are symmetric functions of the sensor decisions. The detection of a known signal in additive Gaussian noise and in Laplacian noise are considered. In both cases, system performance deteriorates when the correlation between the sensor noises is positive and increasing, whereas the performance improves considerably when the correlation is negative and increasing in magnitude.
机译:作者研究了相关噪声对分布式检测系统性能的影响。他们通过假设本地传感器具有相同的工作点,并且传感器观测值的分布是对称的来考虑次优方案。这意味着传感器决策的联合分布以及因此的融合规则是传感器决策的对称函数。考虑在加性高斯噪声和拉普拉斯噪声中检测已知信号。在这两种情况下,当传感器噪声之间的相关性为正并增加时,系统性能都会下降;而当相关性为负数且强度增加时,系统性能会显着提高。

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