Tensor-MODE for multi-dimensional harmonic retrieval with coherent sources

We devise a new method of direction estimation (MODE) based multi-dimensional harmonic retrieval algorithm, which is referred to as tensor-MODE (T-MODE). It is a R-dimensional generalization of the conventional MODE and higher-order singular value decomposition is performed on the tensor observation...

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Bibliographic Details
Published in:Signal processing 2015-03, Vol.108, p.530-534
Main Authors: Wen, Fuxi, So, Hing Cheung
Format: Article
Language:English
Subjects:
Asymptotic properties
Coherence
Combinatorial analysis
Computational efficiency
Harmonics
Higher-order singular value decomposition (HOSVD)
Mathematical analysis
Method of direction estimation (MODE)
Multi-dimensional harmonic retrieval (HR)
Polynomials
Retrieval
Tensor
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Summary:We devise a new method of direction estimation (MODE) based multi-dimensional harmonic retrieval algorithm, which is referred to as tensor-MODE (T-MODE). It is a R-dimensional generalization of the conventional MODE and higher-order singular value decomposition is performed on the tensor observations. Asymptotic efficiency is achieved for the proposed estimator even when the source signals are highly correlated or coherent. Furthermore, the computational cost is reasonable, because it consists of polynomial rooting, followed by a combinatorial search, whereas multi-dimensional optimization is not required. •The method of direction estimation (MODE) is generalized to tensor observations with the use of higher-order singular value decomposition.•The proposed T-MODE is used for multi-dimensional harmonic retrieval.•The asymptotic efficiency of T-MODE is demonstrated for both uncorrelated and coherent sources.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2014.10.009