Dilated Arrays: A Family of Sparse Arrays With Increased Uniform Degrees of Freedom and Reduced Mutual Coupling on a Moving Platform

Li, Shuang; Zhang, Xiaoping

doi:10.1109/tsp.2021.3083988

Cited by 28 publications

(3 citation statements)

References 45 publications

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“…Similarly, placing other sparse arrays on a moving platform also has the same advantages. [15][16][17] design different array structures that can improve the degree of freedom of moving sparse arrays and give their closed expressions. [18,19] propose the conditions and corresponding sampling methods for forming a hole-free differential co-array using a moving sparse array.…”

Section: Introductionmentioning

confidence: 99%

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L₂‐norm with moving coprime arrays

Yang,

Wang,

Cui

et al. 2023

IET Radar Sonar & Navi

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In this article, an effective algorithm is proposed for direction‐of‐arrival (DOA) estimation of coherent signals using the l2‐norm with moving coprime arrays. The proposed algorithm exhibits high accuracy and robustness in decorrelation of coherent signals compared to existing methods. Firstly, the received signal is filtered on the moving coprime array and a signal model is constructed that is compatible with the moving coprime array. Next, virtual sensors is inserted into the holes of the moving coprime array and the received signals are initialised. Then, the Toeplitz matrix is reconstructed based on the covariance matrix of the initial signal and perform low‐rank matrix recovery to eliminate signal coherence by compensating the matrix for zero. Finally, the DOA estimation for the signal is performed using spectral peak search. Simulation results verify that the estimation accuracy of our proposed algorithm outperforms various existing algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L₂‐norm with moving coprime arrays

Yang,

Wang,

Cui

et al. 2023

IET Radar Sonar & Navi

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“…Moreover, to achieve a better DOA estimation performance and reduce the number of receiving channels, sparse arrays have been proposed, such as the nested array [32], coprime array [33,34], etc. In [35], a dilated array is presented and applies the dilation method to other array geometries on a moving platform. Furthermore, for the DOA estimation, some methods have been proposed to reduce the computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Chen,

Zheng

et al. 2022

Preprint

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The conventional direction of arrival (DOA) estimation methods are performed with multiple receiving channels. In this paper, a changeling DOA estimation problem is addressed in a different scenario with only one full-functional receiving channel. A new unmanned aerial vehicle (UAV) swarm system using multiple lifted reconfigurable intelligent surface (RIS) is proposed for the DOA estimation. The UAV movement degrades the DOA estimation performance significantly, and the existing atomic norm minimization (ANM) methods cannot be used in the scenario with array perturbation. Specifically, considering the position perturbation of UAVs, a new atomic norm-based DOA estimation method is proposed, where an atomic norm is defined with the parameter of the position perturbation. Then, a customized semi-definite programming (SDP) method is derived to solve the atomic norm-based method, where different from the traditional SDP method, an additional transforming matrix is formulated. Moreover, a gradient descent method is applied to refine the estimated DOA and the position perturbation further. Simulation results show that the proposed method achieves much better DOA estimation performance in the RIS-aided UAV swarm system with only one receiving channel than various benchmark schemes.

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“…The simple structure efficiently increases the array aperture of non-circular signals, thus broadening the degree of freedom (DOF) of the array [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Projection Constraint Null Broadening and Deepening Method for Conjugate Array

Xiao¹,

Li²,

Wang³

2022

PIER Letters

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The performance of the Capon beamforming sharply decreases against strong directional and large deviation interference. In order to reduce the impact of the abnormal interference, this paper proposes a large degree of freedom null broadening beamforming for non-circular signals. The signal vector is first extended by a uniform linear conjugate array. The covariance matrix of the array is then reconstructed by projection transformation and diagonal loading technique. Finally, the beamforming is constrained by the characteristic subspace of the guide vector matrix, and the analytic expression of the optimal weights of the method is derived. The numerical simulations demonstrate that the proposed null broadening method has the advantages of high degrees of freedom and strong parameter selection robustness.

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Dilated Arrays: A Family of Sparse Arrays With Increased Uniform Degrees of Freedom and Reduced Mutual Coupling on a Moving Platform

Cited by 28 publications

References 45 publications

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L₂‐norm with moving coprime arrays

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L₂‐norm with moving coprime arrays

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Projection Constraint Null Broadening and Deepening Method for Conjugate Array

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Dilated Arrays: A Family of Sparse Arrays With Increased Uniform Degrees of Freedom and Reduced Mutual Coupling on a Moving Platform

Cited by 28 publications

References 45 publications

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L2‐norm with moving coprime arrays

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L2‐norm with moving coprime arrays

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Projection Constraint Null Broadening and Deepening Method for Conjugate Array

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Product

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Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L₂‐norm with moving coprime arrays

Coherent direction of arrival estimation based on low‐rank matrix recovery utilising L₂‐norm with moving coprime arrays