Source localization using a sparse representation framework to achieve superresolution

DOI10.1007/s11045-010-0119-yzbMath1198.94068OpenAlexW2104774765MaRDI QIDQ600881

Chunqi Chang, Qun Wan, Edmund Y. Lam, Xiansheng Guo

Publication date: 3 November 2010

Published in: Multidimensional Systems and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11045-010-0119-y

zbMATH Keywords

resamplingsparsitysource localizationarray signal processingsuperresolutiondirection-of-arrival (DOA)

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Detection theory in information and communication theory (94A13)

Related Items (5)

A new direction-of-arrival estimation method exploiting signal structure information ⋮ Fast DOA estimation of incoherently distributed sources by novel propagator ⋮ Low-complexity 2D parameter estimation of coherently distributed noncircular signals using modified propagator ⋮ Blind DOA and polarization estimation for polarization-sensitive array using dimension reduction MUSIC ⋮ Joint estimation of DOA and polarization based on phase difference analysis of electromagnetic vector sensor array

Uses Software

• PDCO
• SPGL1

Cites Work

• Unnamed Item
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• Greed is Good: Algorithmic Results for Sparse Approximation
• Direction finding for diversely polarized signals using polynomial rooting
• A new DOA estimation technique based on subarray beamforming
• Theoretical Results on Sparse Representations of Multiple-Measurement Vectors
• De-noising by soft-thresholding
• A sparse signal reconstruction perspective for source localization with sensor arrays

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