Synthesis of Sparse Arrays With Discrete Phase Constraints via Mixed-Integer Programming

Synthesizing sparse arrays with discrete phase constraints is a critical problem in many applications. In this letter, we present a novel approach for synthesizing sparse arrays with discrete phase constraints using mixed-integer programming (MIP). The proposed approach optimizes both antenna positi...

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Bibliographic Details
Published in:IEEE antennas and wireless propagation letters Vol. 23; no. 3; pp. 1030 - 1034
Main Authors: Xia, Dongnan, Zhang, Xuejing
Format: Journal Article
Language:English
Published: New York IEEE 01.03.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Convex functions
Discrete phase constraint
Integer programming
Linear programming
Mixed integer
mixed-integer programming (MIP)
Mutual coupling
phase-only reconfigurable array
Phased arrays
Programming
Quantization (signal)
Radar antennas
sparse array synthesis
Sparse matrices
Synthesis
ISSN:1536-1225, 1548-5757
Online Access:Get full text
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Summary:Synthesizing sparse arrays with discrete phase constraints is a critical problem in many applications. In this letter, we present a novel approach for synthesizing sparse arrays with discrete phase constraints using mixed-integer programming (MIP). The proposed approach optimizes both antenna positions and amplitude/phase excitations subject to the given discrete phase constraints. We show that our approach is flexible and can handle various practical constrains, such as minimum spacing constraints between elements, phase-only constraints in reconfigurable arrays. For each scenario, we obtain different MIP formulations, which can be solved using off-the-shelf solvers. Representative simulations are provided to demonstrate the effectiveness and superiority of the proposed method in sparse array synthesis.
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ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2023.3342143