Coherent Source Enumeration With Compact ULAs

Source enumeration typically relies on subspace-based techniques that require accurate separation of signal and noise subspaces. However, prior works do not address coherent sources in small uniform linear arrays, where ambiguities arise in the spatial spectrum. We address this by decomposing the fo...

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Vydané v:IEEE signal processing letters Ročník 32; s. 3077 - 3081
Hlavní autori: Sil, Dibakar, Krishnan, Sunder Ram, Mishra, Kumar Vijay
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Convexity
Covariance matrices
Covariance matrix
Direction-of-arrival estimation
Elliptopes
Enumeration
Estimation
Linear arrays
Matrix decomposition
Noise
Optimization
rank constraint
Sensor arrays
Sensors
smoothing
Smoothing methods
source enumeration
Subspaces
ULA
Vectors
ISSN:1070-9908, 1558-2361
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Shrnutí:Source enumeration typically relies on subspace-based techniques that require accurate separation of signal and noise subspaces. However, prior works do not address coherent sources in small uniform linear arrays, where ambiguities arise in the spatial spectrum. We address this by decomposing the forward-backward smoothed covariance matrix into a sum of a rank-constrained Toeplitz matrix and a diagonal matrix with non-negative entries representing the signal and noise subspaces, respectively. The resulting non-convex optimization problem is solved by proposing T oeplitz a pproach for r ank-based tar g et e s t imation (TARgEt) that employs the alternating direction method of multipliers. Numerical results on both synthetic and real-world datasets demonstrate the effectiveness and robustness of TARgEt over the state-of-the-art.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2025.3593121