Dealing with the detection of the faulty elements of planar antenna arrays with a probabilistic Bayesian compressive sensing (BCS) approach, a key asset for the reliable prediction of the actual status of the antenna under test is the sampling strategy to remotely collect the far-field (FF) data. The aim of this letter is to provide insights into the effectiveness and the reliability of different FF sampling strategies to collect the input data for a state-of-the-art array diagnosis method based on a multitask BCS technique. Representative results are shown to verify the impact of each sampling strategy on the achievable reconstructions.

On the Far-Field Sampling Strategies for Reliable Bayesian Compressive Diagnosis of Planar Arrays / Salucci, M. - In: MICROWAVE AND OPTICAL TECHNOLOGY LETTERS. - ISSN 0895-2477. - STAMPA. - 2022, 64:10(2022), pp. 1828-1835. [10.1002/mop.33373]

On the Far-Field Sampling Strategies for Reliable Bayesian Compressive Diagnosis of Planar Arrays

Salucci, M
2022-01-01

Abstract

Dealing with the detection of the faulty elements of planar antenna arrays with a probabilistic Bayesian compressive sensing (BCS) approach, a key asset for the reliable prediction of the actual status of the antenna under test is the sampling strategy to remotely collect the far-field (FF) data. The aim of this letter is to provide insights into the effectiveness and the reliability of different FF sampling strategies to collect the input data for a state-of-the-art array diagnosis method based on a multitask BCS technique. Representative results are shown to verify the impact of each sampling strategy on the achievable reconstructions.
2022
10
Salucci, M
On the Far-Field Sampling Strategies for Reliable Bayesian Compressive Diagnosis of Planar Arrays / Salucci, M. - In: MICROWAVE AND OPTICAL TECHNOLOGY LETTERS. - ISSN 0895-2477. - STAMPA. - 2022, 64:10(2022), pp. 1828-1835. [10.1002/mop.33373]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/391881
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