进一步讨论EVD方法在方位估计中的最优性

S. Tressens, H. Clergeot, A. Ouamri, M. Bouvet
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引用次数: 2

摘要

对于由EVD和MUSIC算法(或作者在部分相关源的情况下已经引入的扩展)获得的M个源的方位估计的方差,开发了一个通用表达式。与合适形式的Cramer-Rao边界的比较表明,只有当所有信号特征值都远大于噪声电平时,才能达到最优性。该分析扩展到具体的改进,如空间平均或多频率平均,其效果是避免在相关源的情况下出现非常小的特征值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
More on optimality of EVD methods for bearing estimation
A general expression is developed for the variance of bearing estimates of M sources obtained by EVD and the MUSIC algorithm (or an extension of it already introduced by the authors in the case of partially correlated sources). Comparison with a suitable form of the Cramer-Rao bounds demonstrates that optimality is reached only if all signal eigenvalues are much greater than the noise level. The analysis is extended to specific improvements such as spatial averaging or multiple frequency averaging, the effect of which is to avoid the occurrence of very small eigenvalues in the case of correlated sources.<>
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