A Deterministic Far-Field Sampling Strategy for Array Diagnosis Using Sparse Recovery

Li, Wei; Deng, Weibo; Migliore, Marco Donald

doi:10.1109/lawp.2018.2841650

Cited by 32 publications

(21 citation statements)

References 25 publications

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“…Similar approach have also been proposed in near-field measurements [31]. More recently, non-random strategies assuring the RIP property have also proposed [39].…”

Section: Null(a) (Transl)mentioning

confidence: 97%

Near Field Antenna Measurement Sampling Strategies: From Linear to Nonlinear Interpolation

Migliore

2018

Electronics

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The aim of this review paper is to discuss some of the advanced sampling techniques proposed in the last decade in the framework of planar near-field measurements, clarifying the theoretical basis of the different techniques, and showing the advantages in terms of number of measurements. Instead of discussing the details of the techniques, the attention is focused on their theoretical bases to give a gentle introduction to the techniques. For each sampling method, examples on a liner array are discussed to clarify the advantages and disadvantages of the method.

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“…Similar approach have also been proposed in near-field measurements [31]. More recently, non-random strategies assuring the RIP property have also proposed [39].…”

Section: Null(a) (Transl)mentioning

confidence: 97%

Near Field Antenna Measurement Sampling Strategies: From Linear to Nonlinear Interpolation

Migliore

2018

Electronics

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“…As first example let us consider the same ULA with N = 32 radiating elements reported in [29], to which the reader can refer for more details on the simulation procedure. All the elements have unit nominal excitations.…”

Section: Numerical Simulationsmentioning

confidence: 99%

A Hybrid Non-Convex Compressed Sensing Approach for Array Diagnosis Using Sparse Promoting Norm with Perturbation Technique

Deng

Yang

et al. 2018

Electronics

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The use of ℓ p ( 0 < p < 1 ) norm minimization will improve array diagnosis performance provided that the issue of local minima associated to its non-convex nature is properly handled. In order to overcome this deficiency, a hybrid method using random perturbation and non-convex optimization is investigated in this paper. Although it acquires a higher computational time, the trade-off between an accurate diagnosis and the computational burden appears to be acceptable. Theoretical analysis and simulation results demonstrate that the proposed method overcomes this disadvantage effectively and achieves better performance compared to the standard ℓ 1 norm minimization with a smaller number of far-field measurements, suggesting that the proposed method can be used to improve the performance of array diagnosis.

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“…It is worth noting that we have a certain degree of control on the RIP by choosing the number and positions of sampling points with some particular principles [19]. More recently, some strategies to assure a deterministic estimation of the RIP has been proposed in the framework of linear array diagnosis [20]. In terms of the second point, numerous sparse recovery algorithms have been proposed [21,22].…”

Section: Introductionmentioning

confidence: 99%

Fast non‐convex compressed sensing approach for diagnosis of defective array elements using planar near‐field measurements

Deng

Yang

et al. 2019

IET Microwaves, Antennas & Propagation

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A Deterministic Far-Field Sampling Strategy for Array Diagnosis Using Sparse Recovery

Cited by 32 publications

References 25 publications

Near Field Antenna Measurement Sampling Strategies: From Linear to Nonlinear Interpolation

Near Field Antenna Measurement Sampling Strategies: From Linear to Nonlinear Interpolation

A Hybrid Non-Convex Compressed Sensing Approach for Array Diagnosis Using Sparse Promoting Norm with Perturbation Technique

Fast non‐convex compressed sensing approach for diagnosis of defective array elements using planar near‐field measurements

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