Planar Array Diagnosis by Means of an Advanced Bayesian Compressive Processing

Salucci, Marco; Gelmini, Angelo; Oliveri, Giacomo; Massa, Andrea

doi:10.1109/tap.2018.2866534

Cited by 48 publications

(36 citation statements)

References 43 publications

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“…Random partial Fourier matrices (RPFMs) have been used for the retrieval via far field data. The Bayesian CS based framework is proposed to provide reliable detections in [18], [26]. In order to detect AUT via magnitude data only, approximations and modifications are provided in [21], [24].…”

Section: Introductionmentioning

confidence: 99%

A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

Xiong

Xiao

2020

IEEE Access

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A diagnosing method for phased antenna array element failures is proposed. The element excitation amplitudes and phases are reconstructed by a compressed sensing based approach, in which the radiated electric fields of the array are sampled by a single fixed receiving antenna. The diagnosing can be processed when the phased array is still in service. Particularly, it can be specialized for detecting faults only. Element excitation phases are designed to follow Bernoulli distribution, which is difficult to be realized in conventional geometric sampling methods. It is capable to provide effective and simultaneous detection for different types of failures with phase control means that are simpler comparing with other methods in which excitation phase adjustment is required. Especially, a two-step detection strategy is proposed to effectively detect phase failures due to faultily short-circuited phase shifters. Numerical results illustrate the effective sensing range of a single receiving antenna. Full-wave simulations validate the diagnosing performance in the presence of mutual couplings between array elements.

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Section: Introductionmentioning

confidence: 99%

A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

Xiong

Xiao

2020

IEEE Access

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“…The introduction of CS to array diagnosis has attracted sustained attention from scholars and engineers in the antenna community during the last few years, with the purpose of reducing the number of sampling points in both the near-field and far-field measurements [10][11][12][13][14][15][16]. Despite the inspiring results within the area of electromagnetics, several fundamental open points still worthy of investigation systematically so as to have a wider adoption and further exploitation of CS potentialities.…”

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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“…The first one is the time required to collect the data on the observation surface using standard near-field set-ups [ 4 ]. With reference to this point, sparse recovery techniques have been recently proposed in the framework of antenna diagnosis from planar near-field measurements [ 5 , 6 , 7 , 8 ] in order to reduce the number of measured data and consequently the measurement time. The method has been successfully tested from data acquired in anechoic chamber [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

A Minimum Rank Approach for Reduction of Environmental Noise in Near-Field Array Antenna Diagnosis

et al. 2019

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A method to filter out the contribution of interference sources in array diagnosis is proposed. The interference-affected near field measured on a surface is treated as a (complex-data) image. This allows to use some modern image processing algorithms. In particular, two strategies widely used in image processing are applied. The first one is the reduction of the amount of information by acquiring only the innovation part of an image, as currently happens in video processing. More specifically, a differential measurement technique is used to formulate the estimation of the array excitations as a sparse recovery problem. The second technique has been recently proposed in video denoising, where the image is split into a low-rank and high-rank part. In particular, in this paper the interference field is filtered out using sparsity as discriminant adopting a mixed minimum 1 norm and trace norm minimization algorithm. The methodology can be applied to both near and far field measurement ranges. It could be an alternative to the systematic use of anechoic chambers for antenna array testing.

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Planar Array Diagnosis by Means of an Advanced Bayesian Compressive Processing

Cited by 48 publications

References 43 publications

A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

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

A Minimum Rank Approach for Reduction of Environmental Noise in Near-Field Array Antenna Diagnosis

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