Most subspace-based algorithms need exact array manifold for direction of arrival (DOA) estimation, while, in practical applications, the gain-phases of different array elements are usually inconsistent, degrading the...
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Most subspace-based algorithms need exact array manifold for direction of arrival (DOA) estimation, while, in practical applications, the gain-phases of different array elements are usually inconsistent, degrading their estimation performance. In this paper, a novel low-complexity 2D DOA and gain-phase error estimation algorithm is proposed by adding auxiliary array elements in a uniform rectangular array (URA). Firstly, the URA is modeled as the Kronecker product of two uniform linear arrays (ULAs) to decouple the 2D DOA estimation. Then, several well-calibrated auxiliary array elements are added in the two ULAs, based on which the rotation invariant factor of the URA destroyed by the gain-phase error is reconstructed by solving constrained optimization problems. Lastly, ESPRIT is used to estimate the 2-D DOA and the gain-phase error coefficients. The closed-form expressions of the estimation CRBs are also derived, providing insight into the impact of gain-phase error on DOA estimation. Simulation results are used to validate the effectiveness of the proposed algorithm and the correctness of the theoretical analysis.
In this paper, we focus on the problem of joint direction-of-departure (DOD) and two-dimensional (2D) direction-of-arrival (DOA) estimation in massive multiple-input multiple-output (MIMO) systems. A novel method for ...
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ISBN:
(纸本)9783319781303;9783319781297
In this paper, we focus on the problem of joint direction-of-departure (DOD) and two-dimensional (2D) direction-of-arrival (DOA) estimation in massive multiple-input multiple-output (MIMO) systems. A novel method for angle estimation is proposed with automatic pairing. The method transforms the element space into the beamspace by employing the property of conjugate centrosymmetric array, such that the angle estimation operates only on the real-valued computation. Then, we utilize the real-valued rotational invariance relationships in beamspace to estimate DOD and 2D DOA in a fresh fashion. Numerical results show that the proposed algorithm provides reduced computational complexity without the loss of estimation accuracy owing to real-valued processing, automatic pairing and computation dimension reduction in massive MIMO systems.
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