To address the problem of expensive computation in traditional two-dimensional (2D) direction of arrival (DOA) estimation, in this paper, we propose a 2D DOA estimation method based on a reduced dimension and root-finding MUSIC algorithm for nested planar arrays (NPAs). Specifically, the algorithm proposed in this paper transforms the problem based on 2D spectral peak search into two one-dimensional estimation problems by reducing the dimension, and then transforms the one-dimensional estimation problem into a problem of polynomial root finding. Finally the parameters are paired to realize the 2D DOA estimation. The proposed algorithm not only performs two root finding operations directly according to the 2D spectral function transformation, avoiding the performance degradation caused by intermediate operations, but can also fully exploit the enlarged array aperture offered by NPAs with reduced computational complexity and no need for virtualization. The superiorities of the proposed algorithm in terms of estimation accuracy and complexity are verified by simulations.
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| http://dx.doi.org/10.3390/s22145220 | DOI Listing |
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Article Synopsis
- Direction of Arrival (DoA) estimation is a critical area in array signal processing, with advancements in algorithms being driven by new metasurface technology and artificial intelligence.
- The study reviews the integration of traditional DoA algorithms with metasurfaces and explores the use of subspace and sparse representation methods to improve wave detection capabilities.
- Lastly, it highlights the challenges and opportunities that arise from merging metasurfaces and AI to enhance DoA detection and hardware implementation.
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