研究目的
Investigating the synthesis of sparse or thinned linear and planar arrays generating reconfigurable multiple real patterns by iterative linear programming.
研究成果
The proposed iterative linear programming method effectively reduces the number of elements in arrays for multiple desired patterns while accurately controlling radiation characteristics. It is applicable to various array geometries and offers significant savings in the number of elements, as validated by several synthesis examples.
研究不足
The method assumes conjugate-symmetrical excitations, which may not exploit the maximum degrees of synthesis freedom and limits the solution space for patterns that do not naturally have conjugate-symmetrical excitations.
1：Experimental Design and Method Selection:
The methodology involves a sequence of reweighted (cid:2)1 optimizations under multiple linear constraints, assuming conjugate symmetric excitations to formulate upper and lower bounds for each pattern as linear inequality constraints. An auxiliary variable is introduced for each element to define the common upper bound of both the real and imaginary parts of multiple excitations for different patterns.
2：Sample Selection and Data Sources:
The study uses examples of linear arrays, rectangular/triangular-grid, and randomly spaced planar arrays to validate the method.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned in the paper.
4：Experimental Procedures and Operational Workflow:
The proposed method is implemented by iteratively performing linear programming to minimize the reweighted (cid:2)1-norm of auxiliary variables for all elements, selecting common elements with multiple sets of optimized amplitudes and phases.
5：Data Analysis Methods:
The effectiveness of the method is validated through synthesis examples, comparing the number of elements and pattern characteristics against specified requirements.
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