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A Low-Complexity Method for Two-Dimensional Direction-of-Arrival Estimation Using an L-Shaped Array
In this paper, a new low-complexity method for two-dimensional (2D) direction-of-arrival (DOA) estimation is proposed. Based on a cross-correlation matrix formed from the L-shaped array, the proposed algorithm obtains the automatic pairing elevation and azimuth angles without eigendecomposition, whi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298763/ https://www.ncbi.nlm.nih.gov/pubmed/28106840 http://dx.doi.org/10.3390/s17010190 |
Sumario: | In this paper, a new low-complexity method for two-dimensional (2D) direction-of-arrival (DOA) estimation is proposed. Based on a cross-correlation matrix formed from the L-shaped array, the proposed algorithm obtains the automatic pairing elevation and azimuth angles without eigendecomposition, which can avoid high computational cost. In addition, the cross-correlation matrix eliminates the effect of noise, which can achieve better DOA performance. Then, the theoretical error of the algorithm is analyzed and the Cramer–Rao bound (CRB) for the direction of arrival estimation is derived . Simulation results demonstrate that, at low signal-to-noise ratios (SNRs) and with a small number of snapshots, in contrast to Tayem’s algorithm and Kikuchi’s algorithm, the proposed algorithm achieves better DOA performance with lower complexity, while, for Gu’s algorithm, the proposed algorithm has slightly inferior DOA performance but with significantly lower complexity. |
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