Pattern-Reconfigurable Sparse Linear Array Synthesis Under Minimum Element Spacing Control by Alternating Sequential Quadratic Programming

A new method called alternating sequential quadratic programming is proposed to synthesize pattern-reconfigurable sparse linear arrays with minimum element spacing control. The method can find the common element positions and multiple sets of excitations for generating multiple reconfigurable patter...

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Bibliographic Details
Published in:IEEE antennas and wireless propagation letters Vol. 22; no. 6; pp. 1271 - 1275
Main Authors: Li, Lin, Guo, Rongxiang, You, Pengfei, Bai, Jingjing, Qin, Pei-Yuan, Liu, Yanhui
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Alternating sequential quadratic programming (ASQP)
Excitation
Indexes
Linear antenna arrays
Linear arrays
Mathematical analysis
minimum spacing constraint
Optimization
pattern synthesis
pattern-reconfigurable array
Phased arrays
Quadratic programming
Reconfiguration
Shape
sparse array
Synthesis
Upper bound
ISSN:1536-1225, 1548-5757
Online Access:Get full text
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Summary:A new method called alternating sequential quadratic programming is proposed to synthesize pattern-reconfigurable sparse linear arrays with minimum element spacing control. The method can find the common element positions and multiple sets of excitations for generating multiple reconfigurable patterns which accurately meet their given upper and lower pattern bounds. In addition, by introducing auxiliary weighting coefficients and collective excitation coefficient vectors and choosing them as optimization variables alternately, the proposed method can appropriately incorporate the minimum element spacing constraint into the pattern synthesis. Synthesized results show that the proposed method can give satisfactory reconfigurable pattern performance but save much more elements compared with some existing methods.
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ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2023.3240031