Improving the resolution performance of eigenstructure-based direction-finding algorithms
Improving the resolution performance of eigenstructure-based direction-finding algorithms
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DOI：
10.1109/icassp.1983.1172124
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发表时间：
1983-04
期刊：
影响因子：
--
通讯作者：
A. J. Barabell
中科院分区：
文献类型：
--
作者：
A. J. Barabell
近年来，基于传感器协方差矩阵的特征结构形成测向谱的算法备受关注。这些算法很有吸引力，因为它们能够在距离很近的发射器上实现Cramer-Rao测向精度界限，只要可用的信噪比（SNR）足够高，可以分辨估计频谱中的两个不同的峰。在本文中，我们提出了几种降低分辨率所需信噪比的方法。第一种方法包括检查谱多项式的根。该技术适用于均匀间隔的传感器阵列。第二种方法利用所谓的信号空间特征向量的特性来定义具有改进的分辨率能力的有理（极零）谱函数。
Recently there has been much interest in algorithms which form a direction-finding spectrum based on the eigenstructure of the sensor covariance matrix. These algorithms are attractive because of their ability to achieve Cramer-Rao direction-finding accuracy bounds for closely spaced emitters, provided the available signal-to-noise (SNR) is high enough to resolve two distinct peaks in the estimated spectrum. In this paper we present several methods for reducing the SNR required for resolution. The first method involves examining the roots of the spectrum polynomial. This technique is applicable when a uniformly spaced sensor array is in use. The second method uses the properties of the so-called signal-space eigenvectors to define a rational (pole-zero) spectrum function with improved resolution capabilities.