DOA estimation in partially correlated noise using low-rank/sparse matrix decomposition

↓ Direkt till sidans innehåll
↓ Direkt till sidans sekundära innehåll (sidomenyn)

Sökning: L773:2151 870X OR L773:9781479914814 > (2014) > DOA estimation in p...

Malek Mohammadi, MohammadrezaKTH,Signalbehandling,ACCESS Linnaeus Centre,Sharif Univ. of Tech, Iran (författare)

DOA estimation in partially correlated noise using low-rank/sparse matrix decomposition

Artikel/kapitelEngelska2014

Förlag, utgivningsår, omfång ...

IEEE Computer Society,2014
printrdacarrier

Nummerbeteckningar

LIBRIS-ID:oai:DiVA.org:kth-144612
https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-144612URI
https://doi.org/10.1109/SAM.2014.6882419DOI

Kompletterande språkuppgifter

Språk:engelska
Sammanfattning på:engelska

Ingår i deldatabas

SwePubSwePub

Klassifikation

Ämneskategori:ref swepub-contenttype
Ämneskategori:kon swepub-publicationtype

Anmärkningar

QC 20141219
We consider the problem of direction-of-arrival (DOA) estimation in unknown partially correlated noise environments where the noise covariance matrix is sparse. A sparse noise covariance matrix is a common model for a sparse array of sensors consisted of several widely separated subarrays. Since interelement spacing among sensors in a subarray is small, the noise in the subarray is in general spatially correlated, while, due to large distances between subarrays, the noise between them is uncorrelated. Consequently, the noise covariance matrix of such an array has a block diagonal structure which is indeed sparse. Moreover, in an ordinary nonsparse array, because of small distance between adjacent sensors, there is noise coupling between neighboring sensors, whereas one can assume that non-adjacent sensors have spatially uncorrelated noise which makes again the array noise covariance matrix sparse. Utilizing some recently available tools in low-rank/sparse matrix decomposition, matrix completion, and sparse representation, we propose a novel method which can resolve possibly correlated or even coherent sources in the aforementioned partly correlated noise. In particular, when the sources are uncorrelated, our approach involves solving a second-order cone programming (SOCP), and if they are correlated or coherent, one needs to solve a computationally harder convex program. We demonstrate the effectiveness of the proposed algorithm by numerical simulations and comparison to the Cramer-Rao bound (CRB).

Ämnesord och genrebeteckningar

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Signalbehandling hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing hsv//eng
Communication channels (information theory)
Convex programming
Cramer-Rao bounds
Direction of arrival
Signal processing
White noise
Cramer-rao bound (CRB)
Direction-of-arrival estimation
Inter-element spacing
Matrix decomposition
Noise covariance matrix
Second-order cone programming
Sparse representation
Uncorrelated noise

Biuppslag (personer, institutioner, konferenser, titlar ...)

Jansson, MagnusKTH,Signalbehandling,ACCESS Linnaeus Centre(Swepub:kth)u1xdwtcg (författare)
Owrang, ArashKTH,Signalbehandling,ACCESS Linnaeus Centre(Swepub:kth)u18n0o2j (författare)
Koochakzadeh, Ali (författare)
Babaie-Zadeh, Massoud (författare)
KTHSignalbehandling (creator_code:org_t)

Sammanhörande titlar

Ingår i:2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM): IEEE Computer Society, s. 373-3769781479914814

Internetlänk

Hitta via bibliotek

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM) (Sök värdpublikationen i LIBRIS)

Till lärosätets databas

Hitta mer i SwePub

Av författaren/redakt...: Malek Mohammadi, ...; Jansson, Magnus; Owrang, Arash; Koochakzadeh, Al ...; Babaie-Zadeh, Ma ...

Om ämnet

TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Elektroteknik oc ...; och Signalbehandling

Artiklar i publikationen: 2014 IEEE 8th Se ...

Av lärosätet: Kungliga Tekniska Högskolan

Sök utanför SwePub

Sök vidare i:: Google; Google Book Search; Google Scholar

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

LIBRIS.kb.se