An innovative method for the diagnosis of large reflector antennas from far field data in radio astronomical application is presented, which is based on the optimization of the number and the location of the far field sampling points required to retrieve the antenna status in terms of feed misalignments. In these applications a continuous monitoring of the Antenna Under Test (AUT), and its subsequent reassessment, is necessary to guarantee the optimal performances of the radiotelescope. The goal of the method is to reduce the measurement time length to minimize the effects of the time variations of both the measurement setup and of the environmental conditions, as well as the issues raised by the complex tracking of the source determined by a prolonged acquisition process. Furthermore, a short measurement process helps to shorten the idle time forced by the maintenance activity. The field radiated by the AUT is described by the aperture field method. The effects of the feed misalignments are modeled in terms of an aberration function, and the relationship between this function and the Far Field Pattern is recast in the linear map by expanding on a proper set of basis functions the perturbation function of the Aperture Field. These basis functions are determined using the Principal Component Analysis. Accordingly, from the Far Field Pattern, assumed measured in amplitude and phase, the unknown parameters defining the antenna status can be retrieved. The number and the position of the samples is then found by a Singular Values Optimization (SVO). © 2016 AMTA.

Efficient diagnosis of radiotelescopes misalignments / Capozzoli, Amedeo; Curcio, Claudio; Liseno, Angelo; Savarese, Salvatore; Schipani, Pietro. - (2017). (Intervento presentato al convegno Antenna Measurement Techniques Association, AMTA 2016 tenutosi a Austin, TX, USA nel 30 Oct.-3 Nov. 2016) [10.1109/AMTAP.2016.7806287].

Efficient diagnosis of radiotelescopes misalignments

CAPOZZOLI, AMEDEO;CURCIO, CLAUDIO;LISENO, ANGELO;SAVARESE, SALVATORE;
2017

Abstract

An innovative method for the diagnosis of large reflector antennas from far field data in radio astronomical application is presented, which is based on the optimization of the number and the location of the far field sampling points required to retrieve the antenna status in terms of feed misalignments. In these applications a continuous monitoring of the Antenna Under Test (AUT), and its subsequent reassessment, is necessary to guarantee the optimal performances of the radiotelescope. The goal of the method is to reduce the measurement time length to minimize the effects of the time variations of both the measurement setup and of the environmental conditions, as well as the issues raised by the complex tracking of the source determined by a prolonged acquisition process. Furthermore, a short measurement process helps to shorten the idle time forced by the maintenance activity. The field radiated by the AUT is described by the aperture field method. The effects of the feed misalignments are modeled in terms of an aberration function, and the relationship between this function and the Far Field Pattern is recast in the linear map by expanding on a proper set of basis functions the perturbation function of the Aperture Field. These basis functions are determined using the Principal Component Analysis. Accordingly, from the Far Field Pattern, assumed measured in amplitude and phase, the unknown parameters defining the antenna status can be retrieved. The number and the position of the samples is then found by a Singular Values Optimization (SVO). © 2016 AMTA.
2017
9781509051793
Efficient diagnosis of radiotelescopes misalignments / Capozzoli, Amedeo; Curcio, Claudio; Liseno, Angelo; Savarese, Salvatore; Schipani, Pietro. - (2017). (Intervento presentato al convegno Antenna Measurement Techniques Association, AMTA 2016 tenutosi a Austin, TX, USA nel 30 Oct.-3 Nov. 2016) [10.1109/AMTAP.2016.7806287].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/680898
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