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Synthesis of Sparse Array With Sum and Difference Patterns Under Minimum Element Spacing Control by Alternating Linear Programming Optimization
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DOI：10.1109/LAWP.2021.3069907.png)
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Abstract
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A novel method based on alternating linear programming optimization is presented to synthesize sparse linear arrays with sum and difference patterns. This method can find the optimized element positions and excitations shared for both sum and difference patterns with accurate control of multiregion sidelobe distribution and difference pattern null slope. In addition, the constraints on the minimum element spacing and dynamic range ratio of the obtained excitations can be also appropriately incorporated into this alternating optimization process. Two synthesis examples with different pattern shape requirements are conducted to validate the effectiveness and advantages of the proposed method.
Keywords:
Optimization
Minimization
Shape
Upper bound
Programming
Linear antenna arrays
Radar tracking
Alternating linear programming optimization (ALPO)
minimum element spacing control
sparse array
sum and difference patterns
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