In this work, the synthesis problem of sparse linear arrays complying with user defined power masks is addressed by means of a Compressive Sensing (CS)-based methodology. A novel hybrid Bayesian CS (BCS) approach integrating a mask-constrained synthesis within a BCS solver is proposed, enabling an effective and efficient tool for the design of sparse arrays, starting from arbitrary user-defined requirements. A simple example validating the proposed approach is reported and discussed.

Power pattern matching through the hybrid Bayesian compressive sensing / Anselmi, N.; Oliveri, G.; Massa, A.. - STAMPA. - (2018), pp. 1-3. ((Intervento presentato al convegno CAMA 2018 tenutosi a Vasteras, Sweden nel 3rd-6th September 2018 [10.1109/CAMA.2018.8530538].

Power pattern matching through the hybrid Bayesian compressive sensing

Anselmi N.;Oliveri G.;Massa A.
2018

Abstract

In this work, the synthesis problem of sparse linear arrays complying with user defined power masks is addressed by means of a Compressive Sensing (CS)-based methodology. A novel hybrid Bayesian CS (BCS) approach integrating a mask-constrained synthesis within a BCS solver is proposed, enabling an effective and efficient tool for the design of sparse arrays, starting from arbitrary user-defined requirements. A simple example validating the proposed approach is reported and discussed.
2018 IEEE Conference on Antenna Measurements and Applications, CAMA 2018
Piscataway, NJ
Institute of Electrical and Electronics Engineers Inc.
978-1-5386-5795-9
978-1-5386-5796-6
Anselmi, N.; Oliveri, G.; Massa, A.
Power pattern matching through the hybrid Bayesian compressive sensing / Anselmi, N.; Oliveri, G.; Massa, A.. - STAMPA. - (2018), pp. 1-3. ((Intervento presentato al convegno CAMA 2018 tenutosi a Vasteras, Sweden nel 3rd-6th September 2018 [10.1109/CAMA.2018.8530538].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/262121
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