Underdetermined direction of arrival estimation with nested circular ring arrays

Date

2024-8-27

Author

Buğur, Hikmet

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Circular arrays are optimal for achieving an isometric DOA response in planar ge ometries, especially when the inter-element spacing is less than half the operating wavelength. However, in underdetermined scenarios—where the number of sources exceeds the number of sensors—these arrays often experience performance degrada tion due to wider beamwidths and higher sidelobe levels. These limitations are not fully addressed in the existing literature. This thesis introduces a novel array struc ture, the Nested Circular Ring Arrays (NCRA), which combines the benefits of spar sity and circular symmetry to improve DoA estimation accuracy in these challenging cases. NCRA provides a larger effective aperture than traditional circular arrays, resulting in a narrower beamwidth and reduced sidelobe levels, which enhance reso lution and yield more accurate DoA estimates. These improvements allow NCRA to more precisely localize sources compared to a Uniform Circular Array (UCA) with the same number of sensors. The thesis investigates both overdetermined and un derdetermined scenarios, with a particular focus on the challenges posed by coherent sources in underdetermined cases. Techniques such as Maximum Likelihood Estima tion (MLE) for covariance matrices and Sparse Bayesian Learning (SBL) are applied to these scenarios. Additionally, the Khatri-Rao product is used to effectively manage underdetermined cases by mapping observations to a higher dimension. A detailed analysis of NCRA’s design and performance, supported by Cramér-Rao Lower Bound (CRLB) comparisons, demonstrates that NCRA not only maintains isotropic charac teristics but also significantly outperforms conventional circular arrays. This makes NCRA a robust solution for underdetermined DoA estimation, particularly in envi ronments demanding high accuracy and reliability

Subject Keywords

Underdetermined DoA estimation, Sparse bayesian learning, Sparse arrays

URI

https://hdl.handle.net/11511/111549

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Graduate School of Natural and Applied Sciences, Thesis