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Statistical Resolution Limit for multiple parameters of interest and for multiple signals

机译:感兴趣的多个参数和多个信号的统计分辨率极限

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The concept of Statistical Resolution Limit (SRL), which is defined as the minimal separation to resolve two closely spaced signals, is an important tool to quantify performance in parametric estimation problems. This paper generalizes the SRL based on the Cramér-Rao bound to multiple parameters of interest per signal and for multiple signals. We first provide a fresh look at the SRL in the sense of Smith''s criterion by using a proper change of variable formula. Second, based on the Minkowski distances, we extend this criterion to the important case of multiple parameters of interest per signal and to multiple signals. The results presented herein can be applied to any estimation problem and are not limited to source localization problems.
机译:统计分辨率极限(SRL)的概念定义为解析两个紧密间隔的信号的最小间隔,是量化参数估计问题中性能的重要工具。本文基于Cramér-Rao概括了SRL,将其绑定到每个信号和多个信号的多个感兴趣参数。我们首先通过使用适当的变量公式更改,从史密斯准则的角度重新审视SRL。其次,基于Minkowski距离,我们将此标准扩展到每个信号具有多个感兴趣参数的重要情况,并扩展到多个信号。本文介绍的结果可以应用于任何估计问题,并且不仅限于源定位问题。

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