A Sparse-Based Approach for DOA Estimation and Array Calibration in Uniform Linear Array

Liu, Hongqing; Zhao, Luming; Li, Yong; Jing, Xiaorong; Truong, Trieu‐Kien

doi:10.1109/jsen.2016.2577712

Cited by 66 publications

(58 citation statements)

References 29 publications

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“…Besides, we assume that A is unambiguous, i.e., the steering vectors {a(θ i )} N i=1 are linearly independent for any set of distinct {θ i } N i=1 . As described in [27][28][29][30][31][32][33][34][35][36][37][38]43], it may reasonably consider that there are remarkable negative correlation between the coupling strength and the inter-element spacing, and the cross talk effects can be neglected if the distance between two sensors is larger than several times the length of the minimum inter-element spacing d I . By assuming that the minimum inter-element spacing of two sensors without mutual coupling to be Qd I , the generalized MCM can be approximated by…”

Section: Signal Modelmentioning

confidence: 99%

“…However, the mutual coupling effects of the nested array cannot be ignored at least as physical sensors in the inner ULA are deployed relatively close [25][26][27][28][29][30][31][32][33][34][35][36][37][38]. In [39], the super nested array in the context of the second-order statistics is designed to significantly mitigate the cross talk between sensors while preserving all advantages of the standard nested arrays, by increase the inter-element spacing of the inner ULA to maintain the coarray but alleviate the adverse electromagnetic effects.…”

Section: Introductionmentioning

confidence: 99%

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DOA Estimation Using Fourth-Order Cumulants in Nested Arrays with Structured Imperfections

Wang

Zheng

2020

Sensors

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Recently developed super nested array families have drawn much attention owing to their merits on keeping the benefits of the standard nested arrays while further mitigating coupling in dense subarray portions. In this communication, a new mutual coupling model for nested arrays is constructed. Analyzing the structure of the newly formed mutual coupling matrix, a transformation of the distorted steering vector to separate angular information from the mutual coupling coefficients is revealed. By this property, direction of arrival (DOA) estimates can be determined via a grid search for the minimum of a determinant function of DOA, which is induced by the rank reduction property. We also extend the robust DOA estimation method to accommodate the unknown mutual coupling and gain-phase mismatches in the nested array. Compared with the schemes of super nested array families on reducing the mutual coupling effects, the solutions presented in this paper has two advantages: (a) It is applicable to the standard nested arrays without rearranging the configuration to increase the inter-element spacing, alleviating the cross talk in dense uniform linear arrays (ULAs) as well as gain-phase errors in sparse ULA parts; (b) Perturbations in nested arrays are estimated in colored noise, which is significant but rarely discussed before. Simulations results corroborate the superiority of the proposed methods using fourth-order cumulants.

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Section: Signal Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

DOA Estimation Using Fourth-Order Cumulants in Nested Arrays with Structured Imperfections

Wang

Zheng

2020

Sensors

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“…An ℓ 1 -SVDlike method under unknown MC for ULA has been proposed in [9], which takes advantage of the banded symmetric Toeplitz structure of MCM, but this method sacrifices the array aperture so that some array output data is not being used. The authors in [10] studied a joint sparse recovery of DOAs and array perturbation, in which the perturbation matrix is estimated by solving a sparse matrix completion problem. Inspired by the method in [5], an effective block sparse representation model is considered for DOA estimation in the presence of unknown MC for ULA by [11].…”

Section: Introductionmentioning

confidence: 99%

A Novel Block Sparse Reconstruction Method for DOA Estimation With Unknown Mutual Coupling

Zhang

Jiang

et al. 2019

IEEE Commun. Lett.

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In this letter, we consider the direction-of-arrival (DOA) estimation in the presence of unknown mutual coupling in application to uniform linear arrays (ULAs). A novel method is proposed that treats the DOA estimation as a block sparse signal reconstruction problem with a modified array manifold matrix which utilizes the information of entire array output. A block smoothed ℓ 0 norm approximation technique is introduced to solve the problem. Finally, an iterative proximal algorithm is proposed. Simulation results are presented that show the superiority of the proposed method against other known techniques.Index Terms-Direction-of-arrival (DOA), mutual coupling, block sparse reconstruction, block smoothed ℓ 0 (BSL0).

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“…There are plenty of papers talking about mutual coupling effects from different points of view [17]. For example, many mutual coupling correction techniques have been presented in different applications such as direction-of-arrival (DOA) estimation [18][19][20][21][22], adaptive beamforming [23][24][25], antenna array manifold repairment [21,22,26] and static array pattern synthesis [7,12,[27][28][29][30][31]. Due to the significance of the mutual coupling, incorporating the mutual coupling into the pattern synthesis should be very useful.…”

Section: Introductionmentioning

confidence: 99%

Generalisation of genetic algorithm and fast Fourier transform for synthesising unequally spaced linear array shaped pattern including coupling effects

You

Liu

et al. 2017

IET Microwaves, Antennas & Propagation

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Antenna arrays with shaped patterns have drawn significant attention for their wide applications in radar, sonar and communication systems. The combination of genetic algorithm (GA) and fast Fourier transform (FFT) has been used to synthesize shaped pattern of antenna array's factor without considering coupling effects. In this work, the GA-FFT method is generalized by integrating with a new virtual active element pattern expansion (VAEPE) method which approximates each active element pattern as the radiation pattern by exciting several equally spaced virtual elements surrounding the real element position. The generalized GA-FFT can be applicable for the shaped pattern synthesis of unequally spaced linear arrays including mutual coupling and platform effect. Several synthesis examples with different pattern shapes and different antenna structures are given to demonstrate the effectiveness, accuracy and robustness of the proposed method.

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A Sparse-Based Approach for DOA Estimation and Array Calibration in Uniform Linear Array

Cited by 66 publications

References 29 publications

DOA Estimation Using Fourth-Order Cumulants in Nested Arrays with Structured Imperfections

DOA Estimation Using Fourth-Order Cumulants in Nested Arrays with Structured Imperfections

A Novel Block Sparse Reconstruction Method for DOA Estimation With Unknown Mutual Coupling

Generalisation of genetic algorithm and fast Fourier transform for synthesising unequally spaced linear array shaped pattern including coupling effects

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