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A Sparse Uniform Linear Array DOA Estimation Algorithm for FMCW Radar
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AI
DOI：10.1109/LSP.2023.3292739.png)
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Abstract
En 中文
Sparse arrays offer evident advantages over their uniform linear counterparts, including larger aperture and higher angular resolution. Despite their benefits, typical sparse arrays, such as nested and coprime arrays, exhibit increased complexity, and mutual coupling effects between array elements can not be neglected. In contrast, the sparse uniform linear array (SULA) features uniform inter-element spacing, where the distance between elements exceeds half a wavelength, resulting in a larger aperture and reduced mutual-coupling effects. However, estimating the direction of arrival (DOA) with the SULA may lead to inevitable angle ambiguity. Recently, FMCW radar has gained significant attention due to its capability of high-precision ranging under conditions of high signal-to-noise ratios. This study leveraged the high-precision ranging characteristics of FMCW radar to achieve unambiguous DOA estimation by utilizing absolute distance values from targets to each SULA element. Simulation experiments validated the effectiveness of the proposed algorithm.
Keywords:
DOA disambiguation
DOA estimation
FMCW radar
sparse uniform linear array
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W