Detection of sparse targets with structurally perturbed echo dictionaries
Küçük Resim Yok
Tarih
2013
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Academic Press Inc Elsevier Science
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, a novel algorithm is proposed to achieve robust high resolution detection in sparse multipath channels. Currently used sparse reconstruction techniques are not immediately applicable in multipath channel modeling. Performance of standard compressed sensing formulations based on discretization of the multipath channel parameter space degrade significantly when the actual channel parameters deviate from the assumed discrete set of values. To alleviate this off-grid problem, we make use of the particle swarm optimization (PSO) to perturb each grid point that reside in each multipath component cluster. Orthogonal matching pursuit (OMP) is used to reconstruct sparse multipath components in a greedy fashion. Extensive simulation results quantify the performance gain and robustness obtained by the proposed algorithm against the off-grid problem faced in sparse multipath channels. (C) 2013 Elsevier Inc. All rights reserved.
Açıklama
Anahtar Kelimeler
Compressed sensing (CS); Orthogonal matching pursuit (OMP); Cross-ambiguity function (CAF); Particle swarm optimization (PSO); Channel identification; Sparse approximation
Kaynak
Digital Signal Processing
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
23
Sayı
5
