The Ziv-Zakai bound is a well-known lower bound on the minimum mean squared error. This article analyzes the performance of this bound in the practically relevant high-noise regime for a broad family of observation models. The goal is to understand whether this bound is tight, and in which scenarios it should be used. It is shown that, while the Ziv-Zakai bound is tight for a certain class of symmetric distributions, in general, it is not tight in the high-noise regime.

中文翻译：

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Ziv-Zakai 界的高噪声渐近

Ziv-Zakai 界是众所周知的最小均方误差的下界。本文分析了这一界限在广泛的观测模型家族中实际相关的高噪声区域的性能。目标是了解此界限是否严格，以及应在哪些场景中使用。结果表明，虽然 Ziv-Zakai 界对于某一类对称分布来说是紧的，但一般来说，它是在高噪声区不紧。