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Conference Paper (published)

Sparse Linear Array Synthesis Using Exponential Analysis

Details

Citation

Sengupta R, Cuyt A, Prinsloo DS, Nystr?m L & Smolders AB (2023) Sparse Linear Array Synthesis Using Exponential Analysis. In: 2023 IEEE Conference on Antenna Measurements and Applications (CAMA). CAMA, Genoa (Italy), 15.11.2023-17.11.2023, pp. 866-871. https://doi.org/10.1109/CAMA57522.2023.10352694

Abstract
This paper presents an exponential analysis technique for synthesizing a sparse non-uniform linear array using equidistant samples of the array factor of a dense uniform linear array. The problem statement is explored in a realistic production noise setting (i.e., we model uncertainties/tolerances during production as Gaussian noise), which motivates some slight oversampling. The collected samples are organized in the form of a Hankel matrix. A Cadzow iteration provides an accurate lower-rank approximation of the Hankel matrix. This lower-rank Hankel matrix is then used to obtain an equivalent sparse reduced array that accurately approximates the performance of the original dense array. Numerical experiments demonstrate that the newly developed method is more robust and accurate compared to the methods previously reported.

Keywords
EXP; DSP

StatusPublished
Funders我要吃瓜
Publication date31/12/2023
Publication date online31/12/2023
ConferenceCAMA
Conference locationGenoa (Italy)
Dates

People (1)

Professor Annie Cuyt

Professor Annie Cuyt

Honorary Professor, Computing Science and Mathematics - Division