基于渐近阈值排序的MIMO雷达估计简化性能比较度量

Qian He, Xiongwei Wu, Rick S. Blum
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引用次数: 0

摘要

对于许多非线性估计问题,经典下界如Cramer-Rao界(CRB)只能在渐近区域内表征均方误差(MSE)的性能。虽然像Ziv-Zakai界(ZZB)这样更强大的界也可以预测非渐近区域的最佳MSE性能,但它们可能会使计算复杂化到无法承受的程度。在本文中,对于具有良好定义的渐近阈值和几乎相同的CRB的估计量,我们建议使用基于zzb的渐近阈值排序来比较MSE性能。该方法是对CRB的补充,比ZZB更容易计算,为系统的初步设计提供了有效的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation
For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the Ziv-Zakai bound (ZZB) can also predict the best MSE performance in the nonasymptotic region, they may complicate the computation to an unaffordable extent. In this paper, for estimators with well-defined asymptotic threshold and virtually identical CRB, we propose to compare the MSE performance using the ZZB-based asymptotic threshold ranking. This method complements the CRB and is easier to compute than the ZZB, providing an efficient tool for preliminary system design.
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