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Estimation near 'Zero Information' points: angle-of-arrival near the endfire

机译:“零信息”点附近的估算:着火点附近的到达角

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We examine large-sample properties of the maximum- likelihood estimator (MLE) in the vicinity of points where the Fisher information measure (FIM) equals zero. Under mild regularity conditions the MLE is asymptotically efficient and therefore lower bounded by the Cramer-Rao lower bound (CRLB) [5], which diverges for such points. When a linear sensor array is used for angle-of-arrival (AOA) estimation, the CRLB diverges as the AOA approaches pi/2. We provide new results characterizing the MLE performance in the AOA problem.
机译:我们在Fisher信息测度(FIM)等于零的点附近检查最大似然估计器(MLE)的大样本属性。在适度的规律性条件下,MLE渐近有效,因此由Cramer-Rao下界(CRLB)限定下界[5],对于这些点有分歧。当线性传感器阵列用于到达角(AOA)估计时,CRLB随着AOA接近pi / 2而发散。我们提供了表征AOA问题中MLE性能的新结果。

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