Non-uniform L-shaped array consisting of two nested arrays and its computationally efficient two-dimensional direction-of-arrival (dOA) estimationmethod are developed in this study. The basic idea of the proposed met...
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Non-uniform L-shaped array consisting of two nested arrays and its computationally efficient two-dimensional direction-of-arrival (dOA) estimationmethod are developed in this study. The basic idea of the proposedmethod is to utilise the property of nested arrays and the conjugate symmetry property of the signal auto-correlation function for different time lags to construct a conjugate augmented spatial-temporal cross-correlation matrix (CAST-CCM) and form joint diagonalisation structure from the signal subspace corresponding to the CAST-CCM. Hence, the dOAs are estimated and paired automatically via signal subspace joint diagonalisation technique. The proposedmethod can handle underdetermineddOA estimation with automatic matching anddeal with the angle ambiguity problem when multiple sources have the same azimuth or elevation angles. Meanwhile, the proposedmethod is computationally efficient without multidimensional search. The effectiveness of the proposedmethod is verified through computer simulations.
In this study, a new two-dimensional (2d) direction-of-arrival (dOA) estimationmethod with L-shaped array is proposed based on the sparse representation framework. The basic idea is to transform the 2ddOA estimation...
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In this study, a new two-dimensional (2d) direction-of-arrival (dOA) estimationmethod with L-shaped array is proposed based on the sparse representation framework. The basic idea is to transform the 2ddOA estimation problem into two one-dimensional dOA estimation problems by introducing a new compound electric angle. The compound electric and elevation angles are estimated through solving two sparse recovery problems subsequently. Then the azimuth angle estimation and the angle pairing process are completed simultaneously based on the relationship between the estimated elevation and compound electric angles. Owing to the exploitations of the sparse representation technique and the cross correlation information of the incident signals, the proposedmethod exhibits a superior performance, including higher angle resolution ability and improved robustness against low signal-to-noise ratio or small number of snapshots, as well as not requiring the knowledge of the source number. Numerical simulations are performed to verify its effectiveness.
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