Sparse methods for direction-of-arrival estimation

Zai Yang; Jian Li; Petre Stoica; Lihua Xie

doi:10.1016/B978-0-12-811887-0.00011-0

Sparse methods for direction-of-arrival estimation

Zai Yang
, Jian Li
, Petre Stoica
, Lihua Xie

Nanjing University of Science and Technology
Nanyang Technological University
University of Florida
Uppsala University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

323 Scopus citations

Abstract

Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction information of several electromagnetic waves/sources from the outputs of a number of receiving antennas that form a sensor array. DOA estimation is a major problem in array signal processing and has wide applications in radar, sonar, wireless communications, etc. With the development of sparse representation and compressed sensing, the last decade has witnessed a tremendous advance in this research topic. The purpose of this article is to provide an overview of these sparse methods for DOA estimation, with a particular highlight on the recently developed gridless sparse methods, e.g., those based on covariance fitting and the atomic norm. Several future research directions are also discussed.

Original language	English
Title of host publication	Academic Press Library in Signal Processing, Volume 7
Subtitle of host publication	Array, Radar and Communications Engineering
Publisher	Elsevier
Pages	509-581
Number of pages	73
ISBN (Electronic)	9780128118870
ISBN (Print)	9780128118887
DOIs	https://doi.org/10.1016/B978-0-12-811887-0.00011-0
State	Published - 1 Dec 2017
Externally published	Yes

Keywords

Atomic norm
Covariance fitting
Direction-of-arrival (DOA) estimation
Gridless sparse methods
Off-grid sparse methods
On-grid sparse methods
Vandermonde decomposition of Toeplitz matrices

Access to Document

10.1016/B978-0-12-811887-0.00011-0

Cite this

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AB - Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction information of several electromagnetic waves/sources from the outputs of a number of receiving antennas that form a sensor array. DOA estimation is a major problem in array signal processing and has wide applications in radar, sonar, wireless communications, etc. With the development of sparse representation and compressed sensing, the last decade has witnessed a tremendous advance in this research topic. The purpose of this article is to provide an overview of these sparse methods for DOA estimation, with a particular highlight on the recently developed gridless sparse methods, e.g., those based on covariance fitting and the atomic norm. Several future research directions are also discussed.

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KW - Gridless sparse methods

KW - Off-grid sparse methods

KW - On-grid sparse methods

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Sparse methods for direction-of-arrival estimation

Abstract

Keywords

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