Sparsity-Based Off-Grid DOA Estimation With Uniform Rectangular Arrays

This paper studies the optimal three-dimensional (3-D) antenna array for direction finding when the antenna array is subject to geometric constraint. Two-dimensional (2-D) planar array has been widely used in existing direction finding systems, and the optimal geometry for planar array has also been investigated in existing works. However, the optimal antenna array in the 3-D space, especially when the positions of the antennas are subject to geometric constraint, has not been studied yet. In this paper, a novel approach based on coordinate transformation is proposed for optimal antenna array design in the 3-D space with geometric constraint. Due to geometric constraint, the position of each antenna has only two degreesof-freedom even thought it has three coordinate values, so that coordinate transformation can be used to convert 3-D coordinates of the array elements to 2-D ones. Then, existing optimization approach for 2-D planar array can be applied to address the issue of optimal 3-D antenna array. Simulation results show that the proposed antenna array in this paper can outperform the defacto uniform circular array (UCA) even in the presence of geometric constraint. As a potential application, the result in this paper can be applied to design the high-frequency (HF) direction finding antenna arrays that are placed in mountain area. INDEX TERMS Direction finding, optimal antenna array, three-dimensional antenna array, geometric constraint.

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“…By substituting (25) into (42), the constraint in (11b) can be rewritten, following a similar procedure from (19) to (22), as…”

Section: B Optimal 3-d Array Designmentioning

confidence: 99%

Optimal Three-Dimensional Antenna Array for Direction Finding With Geometric Constraint

Liu

You

et al. 2020

IEEE Access

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“…In this section, we present some numerical results to assess the performance of our algorithm. For a comparison, we investigate the performance of the SOMP and MT-BCS algorithms in the 2D case, the MFOCUSS algorithm for 2D DOA based on the SPM, which we label as MFOC-SP, i.e., the first step of our proposed algorithm, the algorithm in [14] and our proposed algorithm.…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…In MFOC-SP, the regularization parameter λ is set to 0.1. In the algorithm in [14], the parameters are kept the same as those in [14].…”

Section: Numerical Simulationsmentioning

confidence: 99%

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A Novel 2D Off-Grid DOA Estimation Method Based on Compressive Sensing and Least Square Optimization

Lei

et al. 2019

IEEE Access

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For two-dimensional (2D) direction of arrival (DOA) estimation in a uniform rectangular array (URA), the conventional method converts the 2D problem into a one-dimensional (1D) problem; however, the computational complexity is high, and the accuracy is limited by the grid interval. To address this issue, based on sparse representation theory and a separable observation model (SPM), this paper presents a novel off-grid-framework-based 2D DOA estimation approach by designing a modified 2D off-grid model and a solution for the multisnapshot case in the SPM. The proposed algorithm can be divided into two stages. In the first stage, we use a matching pursuit and focal underdetermined system solver (MFOCUSS) algorithm to quickly identify the candidate or potential areas where the true sources may exist. In the second stage, the candidate areas obtained in the first stage are regarded as the initialization. Then, for a specific source, we regard other sources as interference. By using an alternating descent method, we can obtain accurate DOAs. Moreover, based on the equivalence of time delay and spatial spacing, a 2D off-grid method for multisnapshot cases is proposed in this paper. Numerical simulations demonstrate the effectiveness and efficiency of the proposed algorithm.

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“…In last several decades, many researchers have done much effort on DOA estimation problems by some common classical methods, such as multiple signal classification (MUSIC) [2] and estimation of signal parameters via rotational invariance techniques (ESPRIT) [3]. However, these investigations mainly focus on the DOA estimation application with L-shape arrays and uniform rectangular arrays (URAs) [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

Efficient Gridless 2-D Direction-of-Arrival Estimation for Coprime Array Based on Decoupled Atomic Norm Minimization

Guo

et al. 2020

IEEE Access

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This paper presents an efficient gridless sparse reconstruction algorithm for the coprime planar array in two-dimensional (2-D) direction-of-arrival (DOA) estimation problem. According to the equivalent second-order statistic signals derived from the covariance matrix of the coprime planar array, we construct a virtual 2-D difference co-array extended from the coprime line arrays along two directions. The virtual array has a double-sized array aperture leading to an increased number of degree-of-freedoms (DOFs). To address the discontinuity of the virtual planar array, and to reduce the computation complexity for the increased array size, decoupled atomic norm minimization approach is investigated to interpolate the missing sensors without discarding any virtual sensors. The problem of decoupled atomic norm minimization can be solved by semidefinite programming with significantly lower computational cost. Besides, the ratio of the number of missing sensors to full sensors in the interpolated virtual uniform array is smaller than that of the physical coprime array, which further improves the recovery accuracy of decoupled atomic norm minimization algorithm. The numerical examples are provided to demonstrate the practical ability of the proposed method in terms of DOF, computational complexity, and DOA estimation error. INDEX TERMS Coprime planar array, decoupled atomic norm, direction-of-arrival (DOA), degree-of-freedom (DOF).

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Sparsity-Based Off-Grid DOA Estimation With Uniform Rectangular Arrays

Cited by 25 publications

References 16 publications

Optimal Three-Dimensional Antenna Array for Direction Finding With Geometric Constraint

Optimal Three-Dimensional Antenna Array for Direction Finding With Geometric Constraint

A Novel 2D Off-Grid DOA Estimation Method Based on Compressive Sensing and Least Square Optimization

Efficient Gridless 2-D Direction-of-Arrival Estimation for Coprime Array Based on Decoupled Atomic Norm Minimization

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