On the Cramer-Rao Bound and the Number of Resolvable Sources in the Presence of Nonuniform Noise for Underdetermined DOA Estimation

被引：1

作者：

Liang, Yibao ^{[1
]}

Liu, Wei ^{[2
]}

Shen, Qing ^{[1
]}

Cui, Wei ^{[1
]}

Wu, Siliang ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China

[2] Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 4ET, S Yorkshire, England

来源：

PROCEEDINGS OF 2020 IEEE 15TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP 2020) | 2020年

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Cramer-Rao bound (CRB); direction-of-arrival (DOA) estimation; underdetermined; sparse array; nonuniform noise; OF-ARRIVAL ESTIMATION; NESTED ARRAYS; DIRECTION; IDENTIFIABILITY;

D O I：

10.1109/ICSP48669.2020.9321004

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, the closed-form stochastic Cramer-Rao Bound (CRB) expression for underdetermined direction-of-arrival (DOA) estimation is derived in the presence of nonuniform noise. By examining the information regularity condition and the number-of-equations condition, it is found that the number of resolvable uncorrelated sources exploiting sparse arrays is upper bounded by the number of positive sensor positions in the virtual difference co-array, which is identical to those in the presence of uniform noise. This indicates that the redundant sensor positions in the difference co-array can provide extra degrees of freedoms (DOFs) for identifiability of more unknown parameters associated with the covariance matrix of the noise, without sacrificing the number of resolvable sources.

引用

页码：93 / 98

页数：6

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