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Resolving manifold ambiguities in direction-of-arrival estimation for nonuniform linear antenna arrays

Identifieur interne : 006E40 ( PascalFrancis/Curation ); précédent : 006E39; suivant : 006E41

Resolving manifold ambiguities in direction-of-arrival estimation for nonuniform linear antenna arrays

Auteurs : Yu. I. Abramovich [Australie] ; N. K. Spencer [Australie] ; A. Y. Gorokhov [France]

Source :

RBID : Pascal:99-0497851

Descripteurs français

English descriptors

Abstract

This paper addresses the problem of ambiguities in direction-of-arrival (DOA) estimation for nonuniform (sparse) linear arrays. Usually, DOA estimation ambiguities are associated with linear dependence among the points on the antenna array manifold, that is, the steering vectors degenerate so that each may be expressed as a linear combination of the others. Most nonuniform array geometries, including the so-called "minimum-redundancy" arrays, admit such manifold ambiguities. While the standard subspace algorithms such as MUSIC fail to provide unambiguous DOA estimates under these conditions, we demonstrate that this failure does not necessarily imply that consistent and asymptotically effective DOA estimates do not exist. We demonstrate that in most cases involving uncorrelated Gaussian sources, manifold ambiguity does not necessarily imply nonidentifiability; most importantly, we introduce algorithms designed to resolve manifold ambiguity. We also show that for situations where the number of sources exceeds the number of array sensors, a new class of locally nonidentifiable scenario exists.
pA  
A01 01  1    @0 1053-587X
A03   1    @0 IEEE trans. signal process.
A05       @2 47
A06       @2 10
A08 01  1  ENG  @1 Resolving manifold ambiguities in direction-of-arrival estimation for nonuniform linear antenna arrays
A11 01  1    @1 ABRAMOVICH (Yu. I.)
A11 02  1    @1 SPENCER (N. K.)
A11 03  1    @1 GOROKHOV (A. Y.)
A14 01      @1 Cooperative Research Centre for Sensor Signal and Information Processing (CSSIP) @2 Adelaide @3 AUS @Z 1 aut. @Z 2 aut.
A14 02      @1 Laboratoire des Signaux et Systèmes, Ècole Supérieure d'Electricité @2 Paris @3 FRA @Z 3 aut.
A20       @1 2629-2643
A21       @1 1999
A23 01      @0 ENG
A43 01      @1 INIST @2 222E3 @5 354000089884210010
A44       @0 0000 @1 © 1999 INIST-CNRS. All rights reserved.
A45       @0 40 ref.
A47 01  1    @0 99-0497851
A60       @1 P
A61       @0 A
A64 01  1    @0 IEEE transactions on signal processing
A66 01      @0 USA
C01 01    ENG  @0 This paper addresses the problem of ambiguities in direction-of-arrival (DOA) estimation for nonuniform (sparse) linear arrays. Usually, DOA estimation ambiguities are associated with linear dependence among the points on the antenna array manifold, that is, the steering vectors degenerate so that each may be expressed as a linear combination of the others. Most nonuniform array geometries, including the so-called "minimum-redundancy" arrays, admit such manifold ambiguities. While the standard subspace algorithms such as MUSIC fail to provide unambiguous DOA estimates under these conditions, we demonstrate that this failure does not necessarily imply that consistent and asymptotically effective DOA estimates do not exist. We demonstrate that in most cases involving uncorrelated Gaussian sources, manifold ambiguity does not necessarily imply nonidentifiability; most importantly, we introduce algorithms designed to resolve manifold ambiguity. We also show that for situations where the number of sources exceeds the number of array sensors, a new class of locally nonidentifiable scenario exists.
C02 01  X    @0 001D04A04A2
C03 01  X  FRE  @0 Traitement signal @5 01
C03 01  X  ENG  @0 Signal processing @5 01
C03 01  X  SPA  @0 Procesamiento señal @5 01
C03 02  X  FRE  @0 Antenne réseau @5 02
C03 02  X  ENG  @0 Antenna array @5 02
C03 02  X  SPA  @0 Antena red @5 02
C03 03  X  FRE  @0 Barrette linéaire @5 03
C03 03  X  ENG  @0 Linear array @5 03
C03 03  X  SPA  @0 Barreta lineal @5 03
C03 04  X  FRE  @0 Ambiguité @5 04
C03 04  X  ENG  @0 Ambiguity @5 04
C03 04  X  SPA  @0 Ambiguedad @5 04
C03 05  X  FRE  @0 Signal gaussien @5 05
C03 05  X  ENG  @0 Gaussian signal @5 05
C03 05  X  SPA  @0 Señal gaussiana @5 05
C03 06  X  FRE  @0 Rapport signal bruit @5 06
C03 06  X  ENG  @0 Signal to noise ratio @5 06
C03 06  X  SPA  @0 Relación señal ruido @5 06
C03 07  X  FRE  @0 Nonidentifiabilité @4 INC @5 72
C03 08  X  FRE  @0 MUSIC @4 INC @5 73
C03 09  X  FRE  @0 Direction arrivée @4 CD @5 96
C03 09  X  ENG  @0 Direction of arrival @4 CD @5 96
C03 10  X  FRE  @0 Réseau non uniforme @4 CD @5 97
C03 10  X  ENG  @0 Nonuniform array @4 CD @5 97
N21       @1 319

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