Reweighted l1Norm Optimization-Based Design of Cross MIMO Arrays for Near-Field Imaging

Guangnan Xing; Shiyong Li; Shuoguang Wang; Rike Jie

doi:10.1109/LAWP.2024.3354918

Reweighted l₁Norm Optimization-Based Design of Cross MIMO Arrays for Near-Field Imaging

Guangnan Xing, Shiyong Li^*, Shuoguang Wang, Rike Jie

^*Corresponding author for this work

School of Integrated Circuits and Electronics

Research output: Contribution to journal › Article › peer-review

Abstract

A sparse array synthesis (SAS) method for cross multiple-input-multiple-output (MIMO) array in near-field imaging is proposed in this letter. We first formulate the MIMO-SAS model as a stepwise optimization of the orthogonally distributed transmit and receive arrays. In each step, a modified reweighted l1 norm regularization is utilized to suppress the sidelobe levels. To avoid broadening of the main lobe, we set a strip focusing area at a specified distance in the direction of the array. The width of the focusing area is adjusted to balance the levels of resolution and sidelobes. Simulations and experimental results demonstrate the superiority of the array synthesized by the proposed method when compared with other state-of-the-art sparse arrays with the same number of antennas.

Original language	English
Pages (from-to)	1316-1320
Number of pages	5
Journal	IEEE Antennas and Wireless Propagation Letters
Volume	23
Issue number	4
DOIs	https://doi.org/10.1109/LAWP.2024.3354918
Publication status	Published - 1 Apr 2024

Keywords

Cross array
multiple-input-multiple-output (MIMO)
near-field imaging
sparse array synthesis (SAS)

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10.1109/LAWP.2024.3354918

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title = "Reweighted l1Norm Optimization-Based Design of Cross MIMO Arrays for Near-Field Imaging",

abstract = "A sparse array synthesis (SAS) method for cross multiple-input-multiple-output (MIMO) array in near-field imaging is proposed in this letter. We first formulate the MIMO-SAS model as a stepwise optimization of the orthogonally distributed transmit and receive arrays. In each step, a modified reweighted l1 norm regularization is utilized to suppress the sidelobe levels. To avoid broadening of the main lobe, we set a strip focusing area at a specified distance in the direction of the array. The width of the focusing area is adjusted to balance the levels of resolution and sidelobes. Simulations and experimental results demonstrate the superiority of the array synthesized by the proposed method when compared with other state-of-the-art sparse arrays with the same number of antennas.",

keywords = "Cross array, multiple-input-multiple-output (MIMO), near-field imaging, sparse array synthesis (SAS)",

author = "Guangnan Xing and Shiyong Li and Shuoguang Wang and Rike Jie",

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AU - Xing, Guangnan

AU - Li, Shiyong

AU - Wang, Shuoguang

AU - Jie, Rike

PY - 2024/4/1

Y1 - 2024/4/1

N2 - A sparse array synthesis (SAS) method for cross multiple-input-multiple-output (MIMO) array in near-field imaging is proposed in this letter. We first formulate the MIMO-SAS model as a stepwise optimization of the orthogonally distributed transmit and receive arrays. In each step, a modified reweighted l1 norm regularization is utilized to suppress the sidelobe levels. To avoid broadening of the main lobe, we set a strip focusing area at a specified distance in the direction of the array. The width of the focusing area is adjusted to balance the levels of resolution and sidelobes. Simulations and experimental results demonstrate the superiority of the array synthesized by the proposed method when compared with other state-of-the-art sparse arrays with the same number of antennas.

AB - A sparse array synthesis (SAS) method for cross multiple-input-multiple-output (MIMO) array in near-field imaging is proposed in this letter. We first formulate the MIMO-SAS model as a stepwise optimization of the orthogonally distributed transmit and receive arrays. In each step, a modified reweighted l1 norm regularization is utilized to suppress the sidelobe levels. To avoid broadening of the main lobe, we set a strip focusing area at a specified distance in the direction of the array. The width of the focusing area is adjusted to balance the levels of resolution and sidelobes. Simulations and experimental results demonstrate the superiority of the array synthesized by the proposed method when compared with other state-of-the-art sparse arrays with the same number of antennas.

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Reweighted l₁Norm Optimization-Based Design of Cross MIMO Arrays for Near-Field Imaging

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