Recent advances of compressive processing (CP) techniques as applied to phased array measurement and direction of arrival (DoA) estimation are presented. Thanks to the CP paradigm, a-priori information on the antenna under test (AUT) can be successfully exploited to mitigate the truncation error in near-field (NF) antenna measurements exploiting a very limited number of measurements. Moreover, Bayesian compressive sensing (BCS) formulations allow to bypass current limitations of standard CS approaches, as well as an easier integration with multi-resolution strategies towards a computationally-efficient and robust DoA estimation. Some numerical results are presented to verify the effectiveness and potentialities of the proposed CP methods.
Compressive Processing for Phased Array Characterization and Direction Finding / Salucci, M.; Hannan, M. A.; Rocca, P.; Migliore, M. D.; Massa, A.. - STAMPA. - (2019), pp. 1-4. (Intervento presentato al convegno 2019 IEEE International Symposium on Phased Array Systems and Technology, PAST 2019 tenutosi a Waltham, MA, USA, nel 15 -18 October,2019) [10.1109/PAST43306.2019.9020898].
Compressive Processing for Phased Array Characterization and Direction Finding
Salucci M.;Hannan M. A.;Rocca P.;Massa A.
2019-01-01
Abstract
Recent advances of compressive processing (CP) techniques as applied to phased array measurement and direction of arrival (DoA) estimation are presented. Thanks to the CP paradigm, a-priori information on the antenna under test (AUT) can be successfully exploited to mitigate the truncation error in near-field (NF) antenna measurements exploiting a very limited number of measurements. Moreover, Bayesian compressive sensing (BCS) formulations allow to bypass current limitations of standard CS approaches, as well as an easier integration with multi-resolution strategies towards a computationally-efficient and robust DoA estimation. Some numerical results are presented to verify the effectiveness and potentialities of the proposed CP methods.File | Dimensione | Formato | |
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