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Statistical Analysis of the Performance of MDL Enumeration for Multiple-Missed Detection in Array Processing

机译:数组处理中多次检测的MDL枚举性能的统计分析

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摘要

An accurate performance analysis on the MDL criterion for source enumeration in array processing is presented in this paper. The enumeration results of MDL can be predicted precisely by the proposed procedure via the statistical analysis of the sample eigenvalues, whose distributive properties are investigated with the consideration of their interactions. A novel approach is also developed for the performance evaluation when the source number is underestimated by a number greater than one, which is denoted as “multiple-missed detection”, and the probability of a specific underestimated source number can be estimated by ratio distribution analysis. Simulation results are included to demonstrate the superiority of the presented method over available results and confirm the ability of the proposed approach to perform multiple-missed detection analysis.
机译:本文针对阵列处理中的源枚举的MDL准则进行了准确的性能分析。通过对样本特征值进行统计分析,可以通过所提出的过程精确预测MDL的枚举结果,并考虑其相互作用来研究其分布特性。当源数被低估了大于一个的数字时,也开发了一种新的性能评估方法,这被称为“多次遗漏检测”,并且可以通过比率分布分析来估计特定的被低估的源数的概率。 。仿真结果包括在内,以证明所提出的方法优于可用结果,并证实了所提出的方法执行多次遗漏检测分析的能力。

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