Aliasing-Free Wideband Beamforming Using Sparse Signal Representation

Sparse signal representation (SSR) is considered to be an appealing alternative to classical beamforming for direction-of-arrival (DOA) estimation. For wideband signals, the SSR-based approach constructs steering matrices, referred to as dictionaries in this paper, corresponding to different frequen...

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Vydáno v:	IEEE transactions on signal processing Ročník 59; číslo 7; s. 3464 - 3469
Hlavní autoři:	Zijian Tang, Blacquiere, G, Leus, G
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.07.2011 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Aliasing Ambiguity Applied sciences Array signal processing Arrays Beamforming Detection, estimation, filtering, equalization, prediction Dictionaries Direction of arrival estimation Exact sciences and technology Information, signal and communications theory Mathematical analysis multiple-dictionary orthogonal matching pursuit Representations Signal and communications theory Signal representation. Spectral analysis Signal representations Signal, noise sparse signal representation spatial aliasing Spatial resolution Telecommunications and information theory uniform linear array Wideband wideband beamforming Parameter estimation Dictionaries Direction-of-arrival estimation multiple-dictionary spatial aliasing Signal estimation uniform linear array Iterative method Signal representation wideband beamforming Algorithm Beam forming orthogonal matching pursuit Wide band Aliasing Matching pursuit Signal processing Sparse representation sparse signal representation Linear antenna arrays
ISSN:	1053-587X, 1941-0476
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Popis
Shrnutí:	Sparse signal representation (SSR) is considered to be an appealing alternative to classical beamforming for direction-of-arrival (DOA) estimation. For wideband signals, the SSR-based approach constructs steering matrices, referred to as dictionaries in this paper, corresponding to different frequency components of the target signal. However, the SSR-based approach is subject to ambiguity resulting from not only spatial aliasing, just like in classical beamforming, but also from the over-completeness of the dictionary, which is typical to SSR. We show that the ambiguity caused by the over-completeness of the dictionary can be alleviated by using multiple measurement vectors. In addition, by considering the uniform linear array (ULA) structure, we argue that if the target signal contains at least two frequencies, whose absolute difference phrased in wavelengths is larger than twice the array spacing, the spatial aliasing corresponding to these frequencies will be completely distinct. These properties enable us to adapt the existing ℓ 1 algorithms to extract the target DOAs without ambiguity.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	1053-587X 1941-0476
DOI:	10.1109/TSP.2011.2140108