n this paper, we present an efficient technique for the synthesis of very large sparse arrays, with arbitrary circularly-symmetrical upper bounds for the pattern specifications. The algorithm, which is based on iterative smooth re-weighted L1 minimizations, is very flexible and is capable of achieving very good performances with respect to competitive algorithms. Furthermore, thanks to its efficiency, planar arrays of hundreds of wavelengths can be synthesized with limited computational effort.
A Structured Deterministic Sampling Strategy for Array Diagnosis from Far-Field Measurements
Migliore, Marco Donald
2018-01-01
Abstract
n this paper, we present an efficient technique for the synthesis of very large sparse arrays, with arbitrary circularly-symmetrical upper bounds for the pattern specifications. The algorithm, which is based on iterative smooth re-weighted L1 minimizations, is very flexible and is capable of achieving very good performances with respect to competitive algorithms. Furthermore, thanks to its efficiency, planar arrays of hundreds of wavelengths can be synthesized with limited computational effort.File in questo prodotto:
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