Vandermonde decomposition of coprime coarray covariance matrix for DOA estimation

Yifan Shen, Chengwei Zhou, Yujie Gu, Hai Lin, Zhiguo Shi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

In this paper, we propose a novel Vandermonde decomposition-based direction-of-arrival (DOA) estimation algorithm by using a coprime array, where increased number of degrees-of-freedom (DOFs) can be achieved in an off-grid manner. Specifically, the equivalent statistics corresponding to an augmented virtual uniform linear array are first derived from the coprime array received signals, and the resulting coprime coarray covariance matrix is capable to increase the DOFs. While the obtained coprime coarray covariance matrix follows a positive semi-definite Hermitian Toeplitz structure, Vandermonde decomposition can be incorporated to perform unique decomposition in the virtual domain. By matching the Vandermonde decomposition result and its theoretical version, closed-form solutions are formulated for estimating the DOA and power of each source. Simulation results demonstrate the effectiveness of the proposed DOA estimation algorithm.

Original languageEnglish
Title of host publication18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781509030088
DOIs
StatePublished - 19 Dec 2017
Externally publishedYes
Event18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017 - Sapporo, Japan
Duration: 3 Jul 20176 Jul 2017

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2017-July

Conference

Conference18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
Country/TerritoryJapan
CitySapporo
Period3/07/176/07/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Funding

This work has been supported by Zhejiang Provincial Natural Science Foundation (No. LR16F010002), National Natural Science Foundation of China (No. U1401253), and the Fundamental Research Funds for the Central Universities (No. 2017QNA5009).

FundersFunder number
National Natural Science Foundation of ChinaU1401253
Natural Science Foundation of Zhejiang ProvinceLR16F010002
Fundamental Research Funds for the Central Universities2017QNA5009

    Keywords

    • Coprime array
    • Degree-of-freedom
    • Direction-of-arrival estimation
    • Vandermonde decomposition
    • Virtual array

    Fingerprint

    Dive into the research topics of 'Vandermonde decomposition of coprime coarray covariance matrix for DOA estimation'. Together they form a unique fingerprint.

    Cite this