Doa估计性能边界的比较

Hung Nguyen, Harry L Van Trees, I. Center
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引用次数: 37

摘要

通过对单个信号的DOA估计MSE的Bayesian crmer - rao下界、Chazan-Ziv-Zakai下界和Weiss-Weinstein下界的数值比较,表明CZZLB是最严密的下界,能够准确预测阈值信噪比,这是系统设计的关键参数。将分析扩展到两个信号,其中多参数WWLB适用,但似乎是一个弱下界。仿真结果表明,在信噪比阈值以下,应采用由交替投影最大化算法(APM)播种的期望最大化(EM)算法等最大似然DOA估计程序,以获得最佳的DOA估计性能。在信噪比阈值以上,使用统计上有效的MUSIC算法是足够的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Performance Bounds for Doa Estimation
For a single signal, numerical comparison of the Bayesian Cramer-Rao lower bound, the Chazan-Ziv-Zakai lower bound and the Weiss-Weinstein lower bound on DOA estimation MSE shows that the CZZLB is the tightest lower bound and can accurately predict the threshold SNR, which is a critical system design parameter. The analysis is extended to two signals where the multiple parameter WWLB is applicable but appears to be a weak lower bound. Simulation results show that below the threshold SNR, a maximum likelihood DOA estimation procedure such as the Expectation Maximization(EM) algorithm seeded by the Alternating Projection Maximization (APM) algorithm should be used to provide the best DOA estimation performance. Above the threshold SNR, the use of the statistically efficient MUSIC algorithm is adequate.
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