Direction of arrival estimation with co-prime arrays via compressed sensing methods

Tianyi Jia, Haiyan Wang, Xiaohong Shen, Xingchen Liu

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

24 Scopus citations

Abstract

In this paper, we consider the problem of direction of arrival (DOA) estimation with co-prime arrays via compressed sensing methods. A sparse signal recovery model based on the framework of co-prime array is presented. We propose to use OMP algorithm to efficiently implement the optimization procedure, which have a lower computational cost. The sparse recovery model of DOA estimation obeys the isotropy property and incoherence property. Therefore, by exploiting the RIPless theory in compressed sensing, we develop the upper bound of degrees of freedom (DOF) of the proposed model. The results establish a basic relationship between upper bound of DOF, the number of samplers and the probability of recovery. Numerical examples show the superiority of the proposed method in detection performance and estimation accuracy compared with the existing spatial smoothing MUSIC algorithm using co-prime arrays.

Original languageEnglish
Title of host publicationOCEANS 2016 - Shanghai
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467397247
DOIs
StatePublished - 3 Jun 2016
EventOCEANS 2016 - Shanghai - Shanghai, China
Duration: 10 Apr 201613 Apr 2016

Publication series

NameOCEANS 2016 - Shanghai

Conference

ConferenceOCEANS 2016 - Shanghai
Country/TerritoryChina
CityShanghai
Period10/04/1613/04/16

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