研究目的
To present an overview of algorithms based on the CS approach for the synthesis of sparse antenna arrays, including additional constraints.
研究成果
The paper concludes that the CS strategy is effective for the synthesis of sparse antenna arrays, allowing for the reduction of the number of elements while meeting far-field and near-field constraints. The approach is versatile and can be extended to include additional constraints such as cross-polar pattern control.
研究不足
The paper does not explicitly discuss limitations, but the approach may be computationally intensive due to the iterative nature of the algorithm and the large number of candidate positions.
1：Experimental Design and Method Selection:
The paper discusses the use of CS techniques for the synthesis of sparse antenna arrays, including the formulation of the problem as a second order cone problem (SOCP) and the use of iterative procedures to achieve sparsity.
2：Sample Selection and Data Sources:
The methodology is applied to antenna arrays with a large number of candidate positions, from which a sparse array is synthesized.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
The paper describes an iterative procedure that at each step solves a weighted l1-minimization problem to achieve sparsity, with constraints on the far-field and near-field patterns.
5：Data Analysis Methods:
The results are analyzed in terms of the synthesized array geometries and corresponding radiation patterns.
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