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Pattern-Reconfigurable Sparse Linear Array Synthesis Under Minimum Element Spacing Control by Alternating Sequential Quadratic Programming
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DOI：10.1109/LAWP.2023.3240031.png)
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Abstract
En 中文
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.
Keywords:
Optimization
Phased arrays
Shape
Quadratic programming
Linear antenna arrays
Indexes
Upper bound
Alternating sequential quadratic programming (ASQP)
minimum spacing constraint
pattern-reconfigurable array
pattern synthesis
sparse array
Journal
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4.8
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1.0W
Citations:
2.8W
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Cited Papers
Synthesizing Unequally Spaced Pattern-Reconfigurable Linear Arrays With Minimum Interspacing Control.png)
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