Fast DOA Estimation Based on the Transform Domain Weighted Noise Subspace Fitting Algorithm for Generalized Sparse Array

Compared with uniform arrays, a generalized sparse array (GSA) can obtain larger array aperture because of its larger element spacing, which improves the accuracy of DOA estimation. At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorith...

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Published inInternational journal of antennas and propagation Vol. 2021; pp. 1 - 10
Main Authors Liu, Chunxi, Chen, Zhikun, Peng, Dongliang
Format Journal Article
LanguageEnglish
Published New York Hindawi 2021
John Wiley & Sons, Inc
Wiley
Subjects
Accuracy
Algorithms
Antennas
Arrays
Computer simulation
Domains
Eigenvalues
Genetic algorithms
Noise
Parameter estimation
Signal classification
Unmanned aerial vehicles
Online AccessGet full text
ISSN1687-5869
1687-5877
1687-5877
DOI10.1155/2021/9952575

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Abstract Compared with uniform arrays, a generalized sparse array (GSA) can obtain larger array aperture because of its larger element spacing, which improves the accuracy of DOA estimation. At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorithms that can be applied to the GSA are unsatisfactory in terms of computational speed and accuracy. To compensate this deficiency, an improved DOA estimation algorithm which can be applied to the GSA is proposed in this paper. First, the received signal model of the GSA is established. Then, a fast DOA estimation method is derived by combining the weighted noise subspace algorithm (WNSF) with the concept of “transform domain” (TD). Theoretical analysis and simulation results show that compared with the traditional multiple signal classification (MUSIC) algorithm and the traditional WNSF algorithm, the proposed algorithm has higher accuracy and lower computational complexity.
AbstractList Compared with uniform arrays, a generalized sparse array (GSA) can obtain larger array aperture because of its larger element spacing, which improves the accuracy of DOA estimation. At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorithms that can be applied to the GSA are unsatisfactory in terms of computational speed and accuracy. To compensate this deficiency, an improved DOA estimation algorithm which can be applied to the GSA is proposed in this paper. First, the received signal model of the GSA is established. Then, a fast DOA estimation method is derived by combining the weighted noise subspace algorithm (WNSF) with the concept of “transform domain” (TD). Theoretical analysis and simulation results show that compared with the traditional multiple signal classification (MUSIC) algorithm and the traditional WNSF algorithm, the proposed algorithm has higher accuracy and lower computational complexity.
Author Liu, Chunxi
Chen, Zhikun
Peng, Dongliang
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Copyright Copyright © 2021 Chunxi Liu et al.
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SubjectTerms Accuracy
Algorithms
Antennas
Arrays
Computer simulation
Domains
Eigenvalues
Genetic algorithms
Noise
Parameter estimation
Signal classification
Unmanned aerial vehicles
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Title Fast DOA Estimation Based on the Transform Domain Weighted Noise Subspace Fitting Algorithm for Generalized Sparse Array
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